CFC/ICAC/37 Final Technical Report

CABI Ref: CFC/ICAC/37
Final Technical Report (December 2009 to December 2013)
Improving cotton production efficiency in smallscale farming systems in East Africa (Kenya and
Mozambique) through better vertical integration of
the supply chain
(CFC/ICAC/37)
Prepared by:
Dr Daniel Karanja (CABI)
Ms Diana Nyamu (CABI)
Dr Waweru Gitonga (KARI - Mwea, Kenya)
Julius Macharia (KARI - Mwea, Kenya)
Mr Helder de Souza (IAM, Mozambique)
Edson Carneiro (IAM, Mozambique)
Mr Martin Kimani (CABI)
Dr Richard Musebe (CABI)
Alex Mungai (CODA, Kenya)
Submitted by:
CABI
P.O. Box 633-00621
Nairobi, Kenya.
June 2014
I. Project Summary
Title:
Improving Cotton Production Efficiency in Small-scale Farming Systems in East
Africa (Kenya and Mozambique) through better vertical integration of the supply
chain
Number: CFC/ICAC/37
PEA:
CABI
PIAs:
Kenya Agricultural Research Institute (KARI)
Instituto do Algodao de Mocambique (IAM)
Supervisory Body: International Cotton Advisory Committee (ICAC)
Participating countries: Kenya and Mozambique
Starting date:
December 2009
Completion date:
December 2013
CFC Financing:
US$ 1,464,600 (Grant)
[EU: Euro 715,000; OPEC Fund contribution (through CFC): US$
250,000; CFC contribution: US$214,600]
Other Financing: N/A
Counterpart financing: US$ 992,400
Kenya: US$562,850
Mozambique: US$307,550
PEA: US$ 122,000)
i
Content
I. Project Summary ..................................................................................................................... i
Content .......................................................................................................................................ii
Acknowledgement and Disclaimer .......................................................................................... iii
Acronyms/Abbreviations .......................................................................................................... iv
List of Figures ........................................................................................................................... vi
List of Tables ...........................................................................................................................vii
List of Boxes .......................................................................................................................... viii
List of Annexes ......................................................................................................................... ix
II. Background and context in which the project was conceived .............................................. 1
2.1 Key commodity issues and relevance to the strategy of the sponsoring International
Commodity Body ................................................................................................................... 1
2.2 Objectives and expected outputs ...................................................................................... 2
2.3 Target beneficiaries and extent of benefits ...................................................................... 3
2.4 Project Costs and Financing............................................................................................. 4
2.5 Project Management and Implementation Arrangements................................................ 4
III. Project Implementation and Results Achieved .................................................................... 6
3.1 Project Implementation .................................................................................................... 8
3.1.1 Best Practice ICM Packages Formulated (Component 1) ........................................ 8
3.1.2. Adoption of ICM Packages Promoted (Component 2) .......................................... 11
3.1.3 Stakeholder Linkages for Sustaining ICM (Component 3) .................................... 24
3.1.4 Impact of ICM Adoption Evaluated (Component 4) .............................................. 29
3.1.5 Project Co-ordination and Management (Component 5) ........................................ 30
3.2 Project Results Achieved ............................................................................................... 33
3.2.1 Extent of use/effect of integrated crop management practices ............................... 33
3.2.2 Cotton production and productivity ........................................................................ 34
3.2.3 Pesticide use in the project area .............................................................................. 36
3.2.4 Contributions of ICM to farmers’ income .............................................................. 36
3.3 Dissemination of Project Results ................................................................................... 37
IV. Lessons Learned ................................................................................................................ 40
4.1 Development Lessons .................................................................................................... 40
4.2 Operational Lessons ....................................................................................................... 40
V. Conclusions and Recommendations ................................................................................... 43
5.1 Conclusions .................................................................................................................... 43
5.2 Recommendations .......................................................................................................... 43
ii
Acknowledgement and Disclaimer
This report is an output of the Project No. CFC/ICAC/37 entitled, “Improving cotton
production efficiency in small-scale farming systems in East Africa (Kenya and
Mozambique) through better vertical integration of the supply chain. CABI was the Project
Executing Agency (PEA), whereas the Kenya Agricultural Research Institute (KARI) and
Instituto do Algodão de Moçambique (IAM) were the Project Implementing Agencies (PIAs).
This project was financed by the Common Fund for Commodities (CFC), an
intergovernmental financial institution established within the framework of the United
Nations, headquartered in Amsterdam, the Netherlands, and by the European Union in the
framework of its “All ACP Agricultural Commodities Programme - AAACP”. Support and
contributions in kind were provided by the governments of Kenya and Mozambique. The
project was developed in consultation with the International Cotton Advisory Committee
(ICAC) which acted as the project’s Supervisory Body (SB), as per CFC’s policies.
The presentation of material in this document and the geographical designations employed do
not imply the expression of any opinion whatsoever on the part of any of the agencies
involved, concerning the legal status of any country, territory, or area, or concerning the
delimitation of its frontiers or boundaries.
iii
Acronyms/Abbreviations
AAACP
ACTIF
AESA
ASAL
BT
CAADP
CABI
CAN
CEO
CFC
CIMSAN
CODA
COMESA
CVCRS
DAAC
DAAC
DNEA
DPA
EAC
EPC
EPZA
EU
FFS
FONPA
GOK
GTI
HVI
IAM
ICAC
ICM
IIAM
IPM
KAM
KAMEA
KARI
KEBS
KEPHIS
KIRDI
MDG(s)
MoA
NEPAD
PCPB
PEA
PIA
PSC
PTD
SADC
SAN/JFS
All African, Caribbean and Pacific (ACP) Agricultural Commodities Programme
African Cotton and Textile Industries Federation
Agro-ecosystem analysis
Arid and Semi-arid Lands
Biotechnology
Comprehensive Africa Agriculture Development Programme
CAB International
Companhia Nacional Algodeira
Chief Executive Officer
Common Fund for Commodities
Centro de Investigação e Multiplicação de Sementes de Algodão de Namialo
Cotton Development Authority (Kenya)
Common Market for Eastern and Southern Africa
Cotton Value Chain Revival Sub-programme, Mozambique
Departamento do Apoio às Associações Camponesas, IAM
Departamento do Apoio às Associações Camponesas, Mozambique
National Directorate for Agricultural Extension (Mozambique)
Directorate of Public Extension (Mozambique)
East African Community
Export promoting Council, Kenya
Export Processing Zones Authority, Kenya
European Union
Farmer Field School
National Cotton Producers Fórum (Mozambique)
Government of Kenya
Government Training Institute, Kenya
High Volume Instrument
Instituto do Algodão de Moçambique
International Cotton Advisory Committee
Integrated Crop Management
Instituto de Investigaçao Agraria de Moçambique
Integrated Pest Management
Kenya Association of Manufacturers
Kenya Apparel Manufacturers Exporters Association
Kenya Agricultural Research Institute
Kenya Bureau of Standards
Kenya Plant Health Inspectorate Services
Kenya Industrial Research and Development Institute
Millennium Development Goal(s)
Ministry of Agriculture, Kenya
New Partnership for Africa's Development
Pest Control Products Board, Kenya
Project Executing Agency
Project Implementing Agency
Project Steering Committee
Participatory Technology Development
Southern African Development Community
Sociedade Algodoeira do Niassa/grupo Joao Fereira dos Santos
iv
SANAM
SB
SDAE
SPS
ToT
Sociedade Algodoeira de Namialo Lda
Supervisory Body
District Directorate of Economic Activities (Mozambique)
Sanitary and Phytosanitary
Training of Trainers
v
List of Figures
Figure 1
Figure 2
Figure 3
Project sites (black circles) in Kenya
Map of Mozambique showing original project sites (left); map of Nampula
Province showing final project sites under Olam-Ribaue (green) and
SANAM (black) concessionaire
Land under cotton production in the project and control (Murupula and
Muecate) districts
vi
6
7
34
List of Tables
Table 1
Table 2
Table 3
Table 4
Table 5
Table 6
Table 7
Table 8
Table 9
Policy issues and suggestions highlighted by farmers/stakeholders in
Mozambique
Policy issues and suggestions highlighted by farmers/stakeholders in Kenya
Training curricula for Farmer Field School facilitators
Agronomy on the Finger Tips: The 5 finger cotton farmer training package
Practical tips for scoring performance of cotton school and farmer fields
Cotton production in the different districts on the farmers’ own fields
(kg/ha.)
Cotton production in the farmer field schools (kg/ha)
Expenditures (money spent) on pesticides (Mt/ha.)
Net income per hectare from cotton production (Meticais)
vii
9
10
11
14
15
34
35
35
36
List of Boxes
Box 1 Criteria for formation of Farmer Field Schools (FFS) and selection of FFS sites
Box 2 Typical Time Table for a Farmer Field School
Box 3 Typical Record Sheet Format for Agro-ecosystem analysis (AESA)
viii
17
21
21
List of Annexes
Annex 1
Annex 2
Annex 3
Annex 4
Annex 5
Annex 6
Annex 7
Annex 8
Annex 9
Project Logframe
Curriculum for training of trainers
Steps in conducting Cotton ICM FFS - The model
Checklist of what one can expect from a quality Farmer Field School (FFS)
Components of cotton ICM in Farmer Field Schools in Mozambique
Market Assistance Programme: Cotton Intervention Logic (Makueni &
Nyanza Ginneries) – Source CODA
Baseline survey report for Kenya
Baseline survey report for Mozambique
Impact assessment report for Mozambique
ix
44
48
51
53
55
57
59
93
124
II. Background and context in which the project was conceived
The project was designed as a pilot project to develop effective and sustainable means to
address the low cotton productivity in Eastern and Southern Africa. It aimed to bridge the gap
between the yield potential of the respective cotton varieties in Kenya and Mozambique and
the low yields obtained at small-holder cotton production units in the two countries. In
consultation with the International Cotton Advisory Committee, the Fund's designated
international commodity body for cotton, CABI was selected as the Project Executing
Agency (PEA). The designated Project Implementing Agencies were Kenya Agricultural
Research Institute (KARI) and Instituto do Algodao de Mocambique (IAM) in Kenya and
Mozambique, respectively. The project aimed to contribute to sustainable increase in cotton
productivity and to lowering the production costs for smallholder cotton farmers in both
countries. Through the use of Integrated Crop Management (ICM), participatory approaches
with intensive farmer involvement, transfer of technology programmes and physical input
supply systems, the project was targeting approximately 50% increase in yield, 50%
reduction in pesticide use and 30% improvement in farmers’ net income.
The project proposal was reviewed by the Fund's Consultative Committee in its 43rd meeting
of January 2009. While acknowledging the relevance of the project, the Committee made
some suggestions to improve the design of the project. The observations made by the
Committee were communicated to the proponents and subsequently addressed in a revised
version of the project proposal, which was reviewed by the Consultative Committee in July
2009. The Executive Board, in its 48th Meeting on 19th to 21st October 2009, took note of the
views and recommendations of the Consultative Committee and approved the Fund's
contribution to the project for a total of up to US$1,535,320. This amount included a
provision for CFC cost for management of the EC co-financing contribution, leaving a total
of up to US$ 1,464,600 available for the project.
2.1 Key commodity issues and relevance to the strategy of the sponsoring
International Commodity Body
Cotton is one of the most important sources of income for smallholders in many of the semiarid regions of Africa. However, profitability for small producers is often marginal due to
yields that are below the potential of varieties grown under rain fed conditions. In Southern
and Eastern Africa, average yields range from 400-750 Kg/ha of seed cotton, while those in
research plots often average 3000 kg/ha and above. Cotton yields are low due for a variety of
reasons including poor quality planting seeds, poor and untimely land preparation, and
inadequate pest control measures. Because of the low production, low productivity and
vulnerability to low cotton prices, farmers often resort to growing alternative crops or
diversify their business in other ways to avoid cotton growing. The project addressed these
constraints by promoting integrated crop management, backed by greater investment in the
provision of technology and associated support services. One way to encourage input and
service delivery by the ginning companies was through a vertically integrated commodity
chain.
The project addressed one of the keys priorities of the Fund's 3rd Five-Year Action Plan,
namely to support the sustainability of smallholder commodity production, thus enabling
small-scale commodity producer to obtain a reasonable income from their production. The
project had a direct beneficiary focus on small-scale cotton producers. The project was
1
endorsed and submitted by the International Cotton Advisory Committee, the designated
international commodity body for cotton. The project fell within the priority programme
"Sustainable Production System with a focus on early stages of the production/processing
chain". The project specifically addressed the stated gap between production efficiency at
research farms and the significantly lower yields obtained in small-holder production
situations.
The project aimed at directly improving farmer income derived from smallholder cotton
production. It envisaged that net farmer income would increase by about 30% (resulting from
yield increase and input reduction). The larger part of the project was directly aimed at
exchanges with immediate beneficiaries in the farmer fields through hands-on training and
dissemination programmes. The project also aimed to strengthen links between farmers and
ginneries that would benefit from increased productivity/production, thus enabling the
ginneries to run with higher level of capacity utilization, and thereby reducing the unit cost of
lint produced. The project worked in close consultation with existing research facilities,
extension programmes, market partners and the identified beneficiaries themselves, to
develop operational, sustainable improved practices which will enable the farmers to secure
higher net incomes from their cotton production.
Poor yield from smallholder cotton in Africa has been a long-standing problem that has not
been altered by release of new varieties or by other recommendations from research findings.
There appear to be a number of problems in translating the outputs from research into the
farmers’ fields. Farmers are consistently not taking up recommendations for a number of
reasons which include:
1. The National Agricultural Research Institutes (NARIs) do not have an adequate system
to ensure that recommendations are promoted and adopted.
2. The recommendations are infrequently updated and if any training manual is produced
it may remain unaltered for many years, so becomes out of date.
3. Some recommendations are based on high input systems and are not presented as
baskets of options from which farmers can select, based on their individual resources
and knowledge.
4. Although on-farm demonstrations have now been recognized as one of the best ways
to build the capacity of farmers in best practice crop management, their numbers are
usually too few to have a large impact.
5. Poor stakeholder coordination
2.2 Objectives and expected outputs
The project goal was to “Reduce rural poverty, improve farmers’ livelihood and promote
sustainability agriculture in cotton based cropping systems in Kenya and Mozambique”. The
project purpose was to improve cotton production efficiency through formulation and
promotion of innovative ICM options in the cotton production systems in Kenya and
Mozambique by involving private enterprises and public organizations. This entailed:
1. Empowering the farming community in on-farm decision making
2. Enhancing skills of smallholders in quality cotton production
3. Raising awareness of farmers about international sanitary and phytosanitary standards
of production procedures of cotton
4. Reducing health hazards to pesticide users and consumers through rationalizing use of
pesticides by developing awareness, training and participatory trials.
2
5. Developing a holistic approach to cotton management and development by
strengthening linkages among service providers and farming communities from presowing to post-harvest management.
2.3 Target beneficiaries and extent of benefits
The participants and beneficiaries of the project were drawn from diverse stakeholder groups
in each of the participating countries including: Cotton producers, Farmers’ associations,
Extension agents, Researchers and their Institutions, Private sector-ginneries, input suppliers,
transporters of cotton, Cotton Bodies (IAM, CODA), Exporters, and Policy makers.
However, the main beneficiaries of the project were the rural households that depend on
cotton production as part or all of their income. The approximate number was 250,000 in
Mozambique. Assuming an average of 5 persons per household, the total number of direct
beneficiaries from improved production efficiency would be around to 1.25 million. A target
of 240 farmer field schools and demonstration plots was planned, 120 each in Kenya and
Mozambique, directly involving a total of approximately 6,000 farmers. It was envisaged that
other farmers would be reached indirectly, through field days and media, among other
dissemination activities.
The project intended to realize the following benefits and impact:
i. Higher yields and more profitable cotton production where farmers implement the
project's ICM systems
Average yield on the farms where the project was being implemented were expected to
increase, with yields in demonstration plots (farmer managed) increasing to at least 50% of
that seen in the best variety in the specific zone in each country. It was anticipated that there
would be an increase of net income of participating farmers from cotton of at least 30% and
this would be realised both from improved production and a reduction in pesticide use (50%).
These three indicators were included in the project logframe at purpose level.
ii. Improved vertical value chain linkages between farmers, private and public sectors
Although numerical targets were not set for this outcome it was expected that the private
sector would make more commitment to the provision of input and technical support to
farmers, the farmers would become better organized and empowered in their bargaining
position vis a vis the private sector, and the public sector would be better able to support both
farmers and ginneries.
iii. Other additional benefits anticipated included:
 Institutional Strengthening: Improved linkages between scientists in the national systems
in the participating countries.
 Poverty Alleviation: The cotton sector already makes a major contribution to the national
economy and to many more livelihoods beyond those of the producers.
 Foreign Exchange Earnings: Improved farmer earnings through reduced input cost and
increased production were also expected to have a positive impact on the foreign exchange
earnings.
The project was thus consistent with CFC and ICAC goals. In terms of CFC priorities as
indicated by the objectives outlined in the Third Five year plan (2008-12), this project
directly addressed the need to improve reliability of supply (Objective 1). The project
allowed an opportunity for the involvement of multinational and national companies
(Objective 9) and highlights the importance of commodities in the economic development
3
and concerns of commodity producers (Objective 10). The formulation and promotion of
innovative gender-responsive ICM options was in tandem with the All ACP Agricultural
Commodities Program (AAACP) strategic objective to “Improve incomes for producers from
traditional or other agricultural commodities and reduce income vulnerability at both
producer and macro level”. The project also addressed key areas of ICAC’s Strategic Plan
which identifies sustainable production systems as one of its strategic areas. It notes that in
most cases the necessary technologies already exist, but because farmers lack knowledge and
access to inputs, implementation is constrained. It is these constraints that the project sought
to address.
2.4 Project Costs and Financing
The total cost of the project was US$ 2,457,000. Of this amount CFC contributed a grant of
up to US$ 1,464,600 whereas the remainder (US$ 992,400) was counterpart contribution (in
kind) provided by the governments of the participating countries (Kenya: US$ 562,850;
Mozambique: US$ 307,550) and the PEA (US$ 122,000). The CFC contribution included cofinancing contribution from European Commission (EC) All ACP Agricultural Commodities
Program (AAACP). A contribution of € 715,000 from the EC was confirmed, out of which
an amount of up to EUR 50,050 (7%) was allocated to cover the Fund’s administrative costs
in connection with its administration of the EC Grant. The actual counter-value of € 715,000
was set at US$ 1,000,000 using the fixed exchange rate of € 1=US$ 1.40. A second
contribution included in the CFC grant was an amount of US$ 250,000 originating from
earmarked contribution of the OPEC Fund for International Development to the Common
Fund's Second Account.
2.5 Project Management and Implementation Arrangements
The Project Executing Agency (PEA) had the overall responsibility for executing the project
including overall co-ordination, with the project budget approved by the Supervisor Body and
the Fund. The PEA, in close collaboration with the Project Implementing Agencies (PIAs) in
Kenya and Mozambique prepared an annual draft work programme and budget including
assignment of tasks. The draft work programme covered, in sufficient detail, the activities to
be carried out during the period by the respective agencies and the PEA. The work
programme included a schedule for reporting by the collaborative agencies. The annual draft
work programme and budget was cleared by ICAC and made available to the CFC with their
comments, before the start of each year. The CFC reviewed and approved the final annual
work programme and budget. The PIAs were responsible for co-ordination of in-country
partners, implementation of agreed activities, preparation and submission of their respective
country reports, with the PEA providing technical backstopping in both countries.
The PIA in Kenya worked in collaboration with the Cotton Development Authority (CODA)
at the national and regional level. CODA staff provided technical support in training of
trainers (ToTs) and farmers, and provision of inputs such as quality seed to participating
farmers. The Kenya Cotton Ginners Association (KCGA) and individual cotton
companies/ginneries (Kitui Ginnery, Salawa Ginnery, Mwea Ginnery, Meru Ginnery, and
Mpeketoni Ginnery) provided staff to be trained during ToT workshops, who thereafter
conducted the season-long training of farmers through Farmer Field Schools (FFS) in
partnership with extension staff from the Ministry of Agriculture.
4
In Mozambique, the PIA worked in collaboration with The Eduardo Mondlane University’s
Department of Crop Production and Plant Protection in the Faculty of Agronomy and Forest
Engineering, which provided technical training inputs. The Instituto do Investigação Agrária
de Moçambique (IIAM) (Mozambique Institute for Agrarian Research) through Centro de
Investigação e Multiplicação de Sementes de Algodão de Namialo (CIMSAN - Cotton
Research and Seed Multiplication Center of Namialo) provided technical capacity (human
resource) for running of the participatory demonstration plots such as on evaluation of
different levels of fertilisers in cotton production, as well as multiplication of basic seed.
Cotton companies, including Sociedade Algodoeira de Namialo Lda/Nampula (SANAM),
China Africa Cotton Mozambique, Companhia Nacional Algodeira (CNA), local farmer
associations (e.g. FOPANA, FANE, FANEMA and FAPIM), and the National Forum of
Cotton producers (FONPA) played a key role in sensitisation of farmers and farmer groups,
in identification of trainees for ToT workshops, and in joint monitoring of FFS activities.
5
III. Project Implementation and Results Achieved
The project activities were clustered under five components
1. Introduction of best practice Integrated Crop Management (ICM) packages
2. Promotion and adoption of ICM packages
3. Building stakeholder linkages for sustaining ICM
4. Evaluation of the impact of ICM adoption
5. Project management and coordination.
Details of the specific activities undertaken and results achieved under each component are
presented in Section 3 of this report, as per the project log-frame.
In Kenya the project was undertaken in the low rainfall cotton growing areas in arid and
semi-arid lands (ASAL) east of the Rift Valley where CODA Cotton Development Authority
(CODA) and KARI have initiated contacts with cotton farmers’ associations and ginneries.
This included Makueni, Kitui, Mwingi, Machakos, Mbeere, Tharaka and Meru North districts
in Eastern Province; Lamu, Taita Taveta, Malindi and Tana River in Coast Province; and
Baringo in the Rift Valley Province (Figure 1).
ETHIOPIA
UGANDA
SOMALIA
Baringo
Meru North
Tharaka
Kisumu
Mbeere
Mwingi
Nairobi
Machakos
Kitui
Kathonzweni
Makueni
Tana River
Lamu
Lamu
TANZANIA
Malindi
Taita
Taveta
Mombasa
Figure 1. Project sites (black circles) in Kenya
In Mozambique, the Project worked with smallholder farmers in Mecuburi, Monapo,
Meconta, Ribaué and Lalaua districts in Nampula Province (Figure 2). Initially the project
had also planned to work in Chemba, Maringue and Caia districts in and Sofala Province.
However, the concession company working in the area, Companhia Nacional Algodeira
(CAN), was taken over by China Africa Cotton Mozambique by end of 2010. The new
concessionaire was unwilling to continue with the project activities hence activities in Sofala
were discontinued (see Section 3.1.1.1).
6
CABO DELGADO
NIASSA
Lalaua
Mecuburi
NAMPULA
Ribaue
Monapo
Nampula
Meconta
ZAMBEZIA
Figure 2. Map of Mozambique showing original project sites (left); map of Nampula Province showing final
project sites under Olam-Ribaue (green) and SANAM (black) concessionaire
7
3.1 Project Implementation
3.1.1 Best Practice ICM Packages Formulated (Component 1)
In this component, the project sought to formulate and introduce an innovative Integrated
Crop Management (ICM) strategy using a Farmer Participatory Training and Research
approach. ICM is a holistic systems approach to increasing the profitability of agricultural
production that incorporates appropriate technologies and best agricultural practices such as
the use of crop rotations, appropriate cultivation techniques, careful choice of seed varieties,
minimum reliance on inputs such as fertilisers and pesticides, better management of on-farm
resources, and environmental conservation. This component had only two indicators: two
training workshops held (indicator 1.1), i.e. one Training of Trainers (ToT) workshop in each
country, and 25 – 30 resource persons trained per ToT (indicator 1.2). The targets for both
indicators were exceeded. In Kenya two ToT workshops were conducted with a total of 30
resource persons having being trained. In Mozambique six ToT workshops were conducted
with a total 174 resource persons having being trained directly by the project. Forty four of
the trainees from Mozambique were trained by the project as master trainers, who further
provided training to another 58 trainers through the cotton revival initiative led by IAM.
3.1.1.1 Participatory analysis of needs and constraints of farmers and markets undertaken
A survey was conducted at the beginning of the project (May - July 2010) to establish the
pre-adoption socio-economic situation and production practices of participating farmers in
the six pilot districts in Kenya i.e. Tharaka South, Kitui Central, Kathonzweni, Lamu West,
Tana Delta and Baringo North. The survey was also undertaken in three control or nonparticipating districts (comparison) districts i.e. Makindu (Eastern Region), Magarini (Coast
Region) and Baringo (Rift Valley Region) where there was no project intervention.
A survey was also conducted (August 2010) in target districts in Sofala (Chemba, Maringue
and Caia) and Nampula (Mecuburi, Monapo and Meconta) provinces in Mozambique.
Following discontinuation of the project activities by China Africa Cotton Mozambique, the
new concessionaire that took over after the exit of Companhia Nacional Algodeira (CAN) in
Chemba, Maringue and Caia districts the project relocated its activities to Ribaué and Lalaua
districts in Nampula. The two districts are within OLAM Ribaue. Subsequently, a situation
analysis was undertaken (August/September 2011) in the two new target districts as well as a
new comparison (control) district (Murupula).
During the surveys in both countries, participatory analysis of needs and constraints of
farmers and markets as well as existing agricultural practices, production patterns and postharvest handling were identified, and details presented in the report annexed to this report.
Some of the issues highlighted by the farmers included low quality seed, pests and the high
cost of pesticides, inadequate knowledge of good cotton production practices, unreliable
rainfall, and inadequate access to inputs (late availability and limited quantities necessitating
alternative systems for the supply/delivery to farmers). Management of pests and diseases
was largely dependent on pesticides, and hence the need to seek alternative and/or
complementary control methods.
The use of integrated crop management strategies was suggested as a good complementary
approach. There were limited crop production technical skills among the cotton growers,
indicating a need for technical support. To provide this support, the cotton
8
companies/ginneries need to invest in providing technical know-how to their field staff, so
that they can advise the cotton growers more effectively.
In terms of marketing, Kenya operates under a free market system in which the cotton
growers purchase their inputs, undertake production and sell the seed cotton to any ginner on
mutually agreed terms. Some farmers may decide to work in collaboration with specific
ginneries, but there is no restriction regarding which company to operate with. However,
there are weaknesses in farmers’ access to market information.
In Mozambique, a concession system is employed, whereby a ginning company is licensed to
operate in a given area and smallholders are obliged to sell to the cotton company operating
in their area. This is meant to protect the ginning company from competition for seed cotton
as they are the sole provider of associated inputs on a credit basis to farmers. This system
does not allow side-selling and is expected to encourage the cotton companies to invest in
provision of inputs, credit and technical support. However, farmers indicated that the returns
from cotton were not adequate to encourage them, especially after deduction of the input
costs.
To improve cotton marketing it was deemed necessary to weigh the cotton with precision and
transparency to avoid suspicion, clearly defining and explaining to the producers the criteria
used to grade seed cotton quality. Farmers also felt there is need for improvement of transport
from the farmers’ field to the company. Finance and/or credit should be supplied in time to
the cotton growers, and payments need to be prompt. It is necessary to encourage
associations/farmers organization to conduct marketing of cotton to the companies on behalf
of the farmers. To empower the associations it is important that payments are made for the
services they provide to the companies (Annexes 6- 7.
The changes in the policy and regulatory issues suggested by farmers/stakeholders are
provided in Tables 1 and 2 for Mozambique and Kenya, respectively.
Table 1. Policy issues and suggestions highlighted by farmers/stakeholders in Mozambique
Practices
Cotton production
Policy and regulatory issues
 Regular review of the concession system with
regard to efficiency in service delivery. Supervising
the distribution and use of seed, pesticides and other
inputs to maintain quality. Ensuring cotton grower
access to the necessary technical know-how
Post-harvest handling
 The cotton company should direct the cotton
growers the types of post-harvest handling
procedures to be undertaken and the necessary
timing. Verify that producers are doing the cutting
and burning.
 Surveillance of the weighing process, overseeing
the sorting, grading and packaging processes.
Marketing
Environment
 Require producers to properly burn or bury
pesticide containers and used batteries; wash
sprayers in provided areas. There is need for a unit
to collect empty pesticide containers for disposal
9
Remarks
 The producers need to be
allowed to sell seed
cotton on a competitive
basis. This may involve
other buyers given the
assurance of repayment
of credit
 Prevent the use of seed
from the previous season
campaign. Farmers
should be encouraged to
use newly provided seed.
 Companies to be
monitored by the
government to assure
maximum benefits to
farmers
 Identify suitable
authorities to handle
spraying process
Practices
Labour regulation
Policy and regulatory issues
 Impose discipline during the spraying and after this
operation, provide protection for the farmers
Remarks
Table 2. Policy issues and suggestions highlighted by farmers/stakeholders in Kenya
Practices
Cotton production
Post-harvest
handling
Marketing
Environment
Policy and regulatory issues
 Provision of inputs (subsidies or
credit) by consensus agreements
between farmers and input
suppliers
 Availing certified seeds:
provision/sale by seed
merchants
 Impartation of technical skills to
farmers
 Use of recommended materials
at harvest and packaging
 Calendar for harvest time and
storage conditions
 Strict requirement of seed
cotton grading
 Participatory marketing
calendar for buying
 Designation of buying centres
 No zoning of ginners’ seed
cotton buying - enhance
competition
 Buying schedules
 Registration of buyers
 Setting of guiding price
 Direct marketing/no agents
 Calibration of scales
 Closed season
 Disposal of pesticide containers
 Use of protective gear
 Labeling of chemicals
Remarks/Improvements
 Create an affordable credit or input provision
scheme/s (pesticides and applicators)
 Assist formation and strengthening of farmer
organizations
 Support seed merchants to undertake
production of certified cotton seed.
 Improve access to the materials
 Address affordability of the materials
 Streamline the use and re-use of bags
between farmers and ginners
 Enforcement of calendar and harmonization
of planting per region
 Capacity building on quality control and
setting up traceability
 Encourage buyers to open stores at the
buying centres during the marketing period
 Avoid contraband chemicals
 Capacity building of users on pesticide
resistance management
 Tamper proof labeling of chemicals and
enhanced supervision by govt. agencies
3.1.1.2. Analysis of farmers’ existing agricultural practices, production patterns, post-harvest
handling conducted
The analysis of farmers’ existing agricultural practices, production patterns, post-harvest
handling was undertaken at the start of the project. This was done during the survey reported
in Section 3.1.1.1. Methods used in production, area under cotton in the various districts,
cotton varieties, characteristics of the cotton growers, access to the factors of production,
processing of cotton and the marketing practices in Kenya and Mozambique are indicated in
subsequent sections.
3.1.1.3 Appropriate ICM models and Training of Trainers curricula formulated
10
A training curriculum for FFS trainers (Annex 2) was developed at the beginning of the
project taking into account the constraints and training needs identified in the target project
sites during the baseline study. Topics included in the curriculum were as below.
Table 3.Training curricula for Farmer Field School facilitators
Cotton ICM Module
Knowledge and abilities acquired by FFS facilitators
Principles of Cotton ICM
Understand and apply the concepts of ICM. Understand
the pros and cons of pesticide usage
Cotton Pests and their
Identify pests affecting cotton and understand various
Management
control methods (chemical, physical, cultural and
biological). Appreciate the ways in which indigenous
knowledge can contribute to ICM.
Cotton Agronomy
Be able advise farmers on best agronomic practices in
cotton farming
Cotton marketing
Understand the various marketing and processing methods
for cotton. Understand policies affecting cotton industry.
Be able to advise farmers on value addition.
Harvesting and Post-harvest
Be able to advise farmers how to harvest and store cotton
handling
without compromising quality. Be able to identify and
describe the different grades of cotton. Be able to advise
farmers on ideal transport and weighing methods.
Cotton Business Management Advise farmers on various sources for obtaining inputs and
credit.
Advise farmers on negotiation of binding contractual
agreements with other stakeholders.
Farmer Field Schools
Understand the farmer field school methodology and
become a good FFS facilitator
Identification of ICM technologies for demonstration in the field days was done through a
participatory process in consultation with cotton experts in the respective countries, extension
staff and participating farmers (Section 3.1.2.2 and Section 3.1.2.4). The TOT modules and
FFS ICM protocols were refined and revised every year based on the experiences and lessons
from the previous seasons.
3.1.1.4 Ginneries supported in the production of quality training and promotional materials
on best ICM strategy
At the project development stage, it was envisaged that the cotton ginneries would be keen to
produce training manuals. However, during consultative meetings with stakeholders in Kenya
and Mozambique it was agreed that this would be done by the researchers and cotton bodies
in the respective countries. The materials developed are presented in Section 3.3.
3.1.2. Adoption of ICM Packages Promoted (Component 2)
The implementation of component 2 was done as per the project work plan (2009-2013) with
a few adjustments on the scheduling of some activities. This component had four indicators:
240 Farmer Field Schools (FFS) established (Indicator 2.1), number of farmers adopting the
formulated ICM package (Indicator 2.2), net income to farmers improved (Indicator 2.3) and
11
50% reduction in pesticides use (Indicator 2.4). During the project period a total of 51 and
159 FFSs were established in Kenya and Mozambique respectively. Thus Mozambique
exceeded the target while Kenya did not, due to budgetary constraints. The majority of
farmers who participated in the project expressed interest in adopting the ICM strategies
promoted by the project, but a formal survey would need to be undertaken to determine the
total number of adopters. Income levels reported by the participating farmers were variable.
In addition, the participating farmers indicated that they were spending less on the pesticides
and the frequency of use of the pesticides was relatively lower among the ICM cotton
growers. However, further validation needs to be undertaken after the end of the project to
confirm any sustained change to production practices.
3.1.2.1 Identify individuals that will act as trainers (facilitators) for the FFS demonstration
plots
Identification of individuals that acted as trainers for the FFSs was done by the PIAs in
collaboration with the local partners in the respective countries. The trainers were identified
and subsequently invited to the ToT workshops reported under Section 3.1.2.2.
3.1.2.2 Conduct training of trainers (ToT) workshops
In Kenya, two ToT workshops were conducted in Embu (August 2010) for FFS facilitators
from Tharaka South, Kitui Central and Kathonzweni Districts. Another ToT workshop was
held in Lamu (November 2010) for FFS facilitators from Tana Delta, Lamu West and
Baringo North Districts The ToT workshops were conducted using the training curriculum
described under Section 3.1.1.4. A total of 30 FFS facilitators, including18 extensionists from
the Ministry of Agriculture, eight farmers, and four from the private sector were trained on
the principles of cotton ICM and FFS methodology. Six district crops officers were also
trained to enable them to coordinate the activities of the FFS facilitators in their respective
districts.
Facilitators being trained on Agro-ecosystem analysis at Mpeketoni Agricultural
Training Centre, Kenya
In Mozambique, a ToT workshop for 30 participants from Nampula and Sofala was
conducted (September 2010) in Beira, Sofala Province using the training curriculum
12
developed in Activity 1.4. The trainees included technicians from cotton companies SANAM
(4) and CNA (5) working directly with farmers within the concessions in Nampula and Sofala
respectively, as well as managers from both companies. Two extensionists from the
Directorate of Public Extension (DPA) in Sofala, three extensionists from the District
Directorate of Economic Activities (SDAE) in Nampula and three extension officers from
three other cotton companies working outside the current project sites(Sociedade Algodoeira
do Niassa/grupo Joao Fereira dos Santos (SAN/JFS), Plexus Mozambique and Chipata
Cotton) also attended the ToT workshop. During the ToT workshop eight agronomists from
IAM central and IAM delegations in Sofala and Nampula were trained as master trainers.
During one of the monitoring and technical backstopping visits to FFSs in Nampula (Section
3.1.2.6) it was noted that the majority of the extension officers from the private companies
were not used to participatory techniques and tools. As a result, CABI’s Farmer Participatory
Training and Research expert and IAM’s National Project Coordinator conducted a refresher
ToT in Nampula in June 2011, to enhance the capacity of the FFS facilitators. The ToT
provided a practical platform to review and validate the running of the FFSs. It included
coaching of facilitators and lead farmer representatives from four local cotton farmers
associations (FOPANA, FANE, FANEMA and FAPIM) as well as the National Forum of
Cotton producers (FONPA). The training included both field and classroom activities.
Refresher hands-on training of trainers in Nampula, Mozambique: Cotton field observation and agroecosystem analysis (AESA) data collection at Escola de Viera Farmer Field School in Meconta
district (top); data processing, report preparation and group discussion (bottom).
One of the major outcomes of the project in Mozambique was the initiation of a nation-wide
programme for establishing FFSs to scale up and out the work initiated by the. This
programme is supported by the government through IAM’s Cotton Revival program being
13
implemented under “Strategic Plan For Developing the Agrarian Sector (PEDSA)”. An
important component of cotton ICM promoted by this project is to support the development
of integrated pest management (IPM) as a preferred way for producers to manage pests of
cotton. To achieve this, the project engaged in extensive capacity development of staff from
the participating institutions, extension workers and staff of ginning companies in Kenya and
Mozambique.
In Mozambique, the PEA and an external consultant (Dr. Ben Sekamatte) conducted two
ToT workshops in Namialo and Nampula in October 2012. The trainees at the workshop held
in Namialo included lead farmers, technicians and facilitators from SANAM and Olam cotton
companies working directly with farmers in the project target areas. The workshop in
Nampula was for master trainers identified by IAM.
The key focus of these two workshops was on the use of five key basic growing practices
(Five Fingers) and Good Agricultural Practices, as well as practical tips for scoring
performance in cotton FFSs (Table 4 and Table 5). These two tools were incorporated in a
revised training manual for Mozambique.
Table 4. Agronomy on the Finger Tips: The 5 finger cotton farmer training package
What Soil Should you grow Cotton on?
 Fertile
 Well drained
 Not water lodged
AVOID
 Cutting primary forests
 Child labour
 Burning of crop residues
 Re –using pesticide containers
IMPORTANT!!
ATTEND COTTON SCHOOL
TRAINING
Early & Proper Land
Preparation
Early & Proper
planting
Finger # 2
Finger # 1
Description
Emphasis
Poor observance leads to:
Recommendation
Prepare fields early
when the soil is still
moist
Allow enough time for
past season residues to
decompose
Ensure a good seedbed
Correct dosage and
spray coverage of preemergence herbicides
Plant as soon as
possible so that cotton
germinates with the
first soaking rains
Late planting
Have your field ready by 15th
May to avoid planting late
and lose yield.
Plant 3-5 treated seeds
/ station in the correct
spacing of 70cm x
Seed wastage is money wasted
Moisture loss
Soil erosion
Poor germination
Poor weed kill exposing cotton
seedlings to early competition
with weeds
Late planted cotton suffers more
pest and disease attacks, smaller
bolls and poor quality fibres
14
Strictly follow instructions
while applying the
recommended herbicides
Have your cotton planted
before the 15th of June to
avoid up to 50% loss of the
potential yield
Correct Plant Population
Check the germination
of the crop & gap fill
where germination
failed within 5 days of
germination of the
main crop.
Thin out to leave 2
strong seedlings per
station within 14 days
after germination
Early weeding
First weeding must be
completed (not
started) before the end
of 14 days after
germination
Efficient pest
management
Finger # 5
Finger # 4
Finger # 3
30cm
Avoid burying the
seed too deep: 1.5 –
3cm soil cover good
Do not leave seed
uncovered on the
ground
Plant seeds in groups
Monitor the
appearance of pests in
the cotton fields from
germination
Delayed or failed seed
germination causes low plant
population
Pests e.g. rats, birds will destroy
the seeds
Scattered seeds suffer delayed
emergence
No yield comes from gaps
Ensure to achieve a plant
population of above 70,000
plants/ha if planted at 90 cm x
30 cm or 75cm x 30.
More than 2 plants per station
are weeds to each other.
The applied 3gm of NPK /
Sulphate of Ammonia per station
becomes inadequate - wasted
Weeds compete with cotton
plants for nutrients, water, light
and space
Weeds harbour pests that
damage the crop and cause yield
and quality loss
If the weeds remain after the
crop reaches 15 days after
emergence they will reduce
yield by 2% per day, which is
about 20 kg / ha per day.
Keep the field weed-free
Weeds also prohibit branching,
which is very important for boll
formation
Weeds contaminate seed cotton
at harvest and may lower lint
grade
Pests cause significant loss of
yield and inefficient control
approaches impact on the
farmers health and that of the
environment
Ensure the judicious use of
pesticides and be sure to
integrate their use with all
other available pest control
alternatives.
Table 5. Practical tips for scoring performance of cotton school and farmer fields
Finger # 1
Finger # Emphasis
Location
Seedbed quality
Residue
management
Check Points
Poor soil fertility
Water lodged
Erosion prone
Large clods
Too fine, bare soil
Visible Impact
Poor crop stand, pale yellow
leaves, loss of top soil
Planting ridges, basins wrongly
positioned
Crop residues burnt
Residues removed from field
15
Gappy crop due to failed
germination, seeds swept away by
heavy first rains
Erosion sweeping away soil, seed /
applied granular fertilizer
Pieces of burnt stalks
Heaps of residues in surrounding
Finger # 2
Finger # Emphasis
Crop rotation
Not practiced
Plant spacing
Inter-row and within rows
spaces
Timely planting
Crop age at time of inspection
Ensure good
seed placement
Crop uniformity
Interplant paces larger / lower
than recommended between
and within the rows
Seeds scattered on the ground /
planted too deep
Uniform crop stand because
gap – filling was completed
within 5-7 days after
germination
Stations without plants confirm
no gap-filling
Clear age differences between
plants confirm delayed gap
filling
All plant stations have 2 plants
of same age because thinning
was completed within 14 days
after germination
Lately thinned, dry seedlings
seen lying within /thrown
outside the field
Presence of weeds
Pale green/yellow plant leaves
Finger #3
Ensure that all
spaces where
germination
failed are
replanted.
Timely thinning
is essential
Finger #4
Keep the field
weed -free
Finger #5
Check Points
Pests must be
efficiently
managed to
safeguard yield
loss
Plants with very long
internodes, with weak branches
above 30cm on the main stem.
Symptoms of pest damage on
leaves, squares and bolls
Square and boll shedding with
evidence of bollworm damage
Visible Impact
bush
Ratoon crops visible
Aphids multiplying on ratoon
plants
Inter-row spaces of 70cm & 30cm
between stations that are lower or
higher are bad and affect plant
population.
Crop age not matching stage of
season e.g. if no bolls at 10 weeks
since start of season – confirm late
planting
Lower or higher assessed plant
population per hectare. In either
situation, yield of seed cotton is
lowered.
More than 2 thin plants per station
competing with each other for
nutrients including fertilizers meant
for ONLY 2 plants
Elongated plants with poor/ no
lower branches , poor boll set due
to early age competition
High pests infestation
Very poor flowering, boll setting,
undersize bolls
Very poor response of plants to the
applied fertilizers
Low counts of squares and bolls
per plant
High numbers of damaged squares
and bolls per plant or per 10 square
meters.
The Cotton ICM/FFS ToT workshop held in October 2012 at Namialo was attended by 62
participants from the target areas of the project. The trainees included lead farmers,
technicians and facilitators from cotton companies SANAM (40) and OLAM - Ribaue (19)
16
working directly with farmers within the concessions in Nampula, one Director of production
from SANAM company, and representatives from 13 local farmer associations and the
National Forum of Cotton Producers (FONPA). One agronomist from IAM central and two
from IAM delegations in Nampula were trained as master trainers. During the ToT, the topic
“Quality control and post-harvest handling” was conducted by a Cotton Fibre Classing
technician from IAM-Headquarters. Forty four participants attended the master trainers
comprising of staff from IAM (20), cotton companies (21) and CIMSAN/IIAM (3). The
master trainers further provided training to another 58 local trainers (October 2012) through
the cotton revival initiative led by IAM within the target areas of the project under SANAM
(36) and OLAM (22) concessions.
3.1.2.3 Selection of demonstration sites from existing FFS
After the training (Section 3.1.2.2), local extension officers from the private companies acted
as farmers’ trainers (facilitators). Together with the smallholder cotton farmers the trained
facilitators were responsible for identification of FFS sites and establishing FFSs (Section
3.1.2.4) in their respective districts in Kenya and Mozambique. The criteria used in formation
of FFS groups and selection of FFS sites is shown in the box below.
Box 1. Criteria for formation of Farmer Field Schools (FFS) and selection of FFS sites
Identification of FFS members










Active farmers and practicing cotton farming
Willingness to participate in FFS
Ready to work in a group
Socially acceptable
Farmers must have a common interest
Farmers must come from the same locality
Must be willing to follow norms set by the group
Must be willing to share experiences
Must be willing to share financial costs, material costs and gains
The FFS group must be open to either gender
FFS site selection
 Accessible by locally available means of transport
 Suitable for the particular enterprise (problem area or technology to be addressed).
 Accessible to all the farmers (democratically selected)
 Have a data processing site. For example a table, stool or log to allow measurements and
proper working. Agree on units of measurements e.g. kilogram/pound, cm/inches,
feet/metres and acre/hectare
 Provision for security on issues like fire, draining excess water.
 Avoid waterlogged areas and steep slopes or over shaded areas. Fenced areas are preferred
especially where the site is adjacent to public utilities like schools or roads.
 Avoid duplication, such as having a FFS plot for sweet potatoes and another for cotton in
the same farm
The number of FFS established and technologies evaluated are presented in Section 3.1.2.4
17
3.1.2.4 Establishment of on-farm demonstration plots within selected FFS
Activities at the various cotton FFSs depend mainly on the time of the cropping season and
stage of growth of the crop (Annexes 3 and 4). In Kenya there are two distinct growing
seasons based on the rainfall pattern. Three of the target districts (Baringo North, Lamu West
and Tana Delta) are located in regions where cotton is normally planted between mid-March
and April, and matures within one rainfall season or about six months. The other three project
districts (Kathonzweni, Tharaka South and Kitui Central) are located in Eastern Kenya,
where cotton is normally planted between mid-October and November and takes two rainfall
seasons to mature, or about 10 - 11 months.
During the project a total of 51 FFSs were established with 30 to 40 members each, in the six
target districts in Kenya. After selection of FFS sites (Section 3.1.2.3) participatory
technology development (PTD) trials were established in Baringo North, Tana Delta and
Lamu West Districts in April/May 2011, based on the cotton cropping season. Establishment
of PTD in Tharaka, Kitui Central and Kathonzweni Districts was undertaken in
October/November 2010 and 2011.
The PTD is a process of joint experimentation and collective investigation through which
communities solve local problems. It empowers both farmers and facilitators with
observational and analytical skills to investigate the cause and effect of major production
problems. It compares farmers’ practices against the new technology (current technology
from research and extension). It allows farmers to make informed decisions, based on their
own observations and records.
The technologies evaluated in the PTD plots as prioritised by the participating farmers
included pest management options, spacing and plant populations, intercropping options, soil
fertility, time of planting and tillage options. Prior to establishment of the PTDs soil samples
were collected and analysed at KARI-Kabete soil survey laboratory to establish the soil
fertility status at the selected FFS sites. With the support of their respective facilitators,
members of each FFS developed a programme for the season-long trainings including the
frequency of meetings to conduct AESAs (see Section 3.1.2.5).
In Mozambique, the cropping season in all the cotton growing regions normally begins in
November/December and ends in June/July. The project established a total of 159 FFSs
reaching 2700 farmers directly in the target project sites in Nampula. Each FFS had two plots
of 0.5 ha each, where one was managed using conventional methods and the other using ICM
practices. Farmers were also encouraged to undertake similar practices on their own farms.
The cotton growers had regular meetings to discuss and share their knowledge and
experience on cotton production, crop protection, post-harvest handling and marketing.
18
Harvesting cotton in Mozambique
The ICM packages evaluated in the FFS in Mozambique included the use of a combination of
IPM practices (Annex 5), spacing, fertilizer (NPK and urea), certified seed (CA 324 and
ALBAR SZ 9314), herbicide (Glyphosate), and strip intercropping comprising of 12 rows of
cotton followed by four rows of another crop, maize or Soybean.
Strip-intercropping of maize and cotton in Mozambique
In addition to training, farmers in the FFS received inputs such as treated cotton seed (variety
CA324 and ALBAR SZ 9314), maize seed, soybean seed, herbicides and pesticides to carry
out the management practices in the FFSs. The Project also distributed ULV sprayers and
protective clothing to the FFS farmers. The farmers in an FFS were divided into smaller
groups of five members to share a sprayer, using the sprayer in rotation. This arrangement
was used as unavailability of sprayers was cited as one of the constraints during the situation
analysis conducted in Component 1. The cotton companies occasionally provided sprayers to
farmers at the beginning of a cropping season, but in those cases 15-20 farmers shared a
19
sprayer. Protective clothing such as boots, nose masks and gloves, were provided to ensure
safety and to raise awareness on the importance of using proper protection while using
hazardous chemicals.
3.1.2.5 Conduct farmer-participatory agro-ecosystem analysis (AESA) at selected
demonstration sites
The FFS in Kenya (Section 3.1.2.3) conducted weekly/fortnightly ICM training and agroecosystem analysis (AESA). The objective of the AESA was to facilitate learning by
discovery in the FFS, and to enable farmers to critically analyse and make better decisions on
their fields. The farmers used the following steps when conducting AESA:
1. Go to the field and ensure a notebook and a pen is ready
2. Each group to look around the field as close and as far as the eye can see. i.e. up to the
furthest horizon
3. List all the living and non-living things that can be observed.
4. Discuss how they are connected and how they affect each other. The discussion takes
about 20 minutes up to a maximum of one hour.
5. Each group to make a picture of all that they saw
6. Presentations by the groups.
Discussion session at FFS site in Kitui Central District, Kenya
20
Box 2. Typical Time Table for a Farmer Field School
Time
09.00-09.10 a.m
09.10-9.45 a.m
09.45-10.15 a.m
10.15-10.45 a.m
10.45-11.45 a.m
11.45-11.55 a.m
11.55-12.00 p.m
Activity
Prayer/IPPM
Recap/Registration
Field monitoring
(AESA)
AESA processing
(presentation)
Dynamics break
Special topic
Planning
Closing prayer
Objective
Material
By who
Host team
Sub-Groups
Sub-Groups
Host team
Facilitator
All
During AESA sessions, farmers took data on pests and natural enemies, plant height, plant
height, seed cotton yield and special topics.
Box 3. Typical Record Sheet Format for Agro-ecosystem analysis (AESA)
NAME OF FFS…………………………
AESA No……………………….
SUB-GROUP No……………………….
DATE……..
WEEK No. …….
TYPE OF
FFS……………………………..
(Staff run, farmer run, farmer sponsored or
donor funded)
PTD PLOT No. …………………….
PROBLEM
ADDRESSED……………………..
GENERAL INFORMATION
PARAMETERS
Variety…………………
Plant Height
Date Planted………..
No. of Nodes
Age of Crop……….
No. of Leaves
Spacing………..
Width of Leaves
Fertiliser Type……….
Length of Leaves
Weather………..
No. of Flowers
Observation Time……….
INSECT - PEST
PLANT DRAWING
NATURAL ENEMIES
OBSERVATIONS
RECOMMENDATIONS
Soil Moisture
Leaf Colour
Pest
Weeds
Plant-Health
Approximately 10-14 AESA sessions were conducted at each site by the end of each
cropping season. Topics covered during the training sessions included: land
preparation/tillage options, time of planting, plant spacing/density, identification of cotton
21
pests and their management options, soil fertility management, weeding, harvesting and
grading of seed cotton and factors affecting lint quality.
Similarly in Mozambique, FFSs in all the target districts conducted AESAs fortnightly during
each cropping season.
3.1.2.6 Mentor and backstop trainers as they train farmers
The project team/master trainers from CABI, KARI and CODA conducted at least two
mentoring and backstopping visits to the FFS sites in Kenya within a cropping season.
During the visits, the different aspects of cotton ICM including PTD design, financial
management and record keeping were revisited.
Mentoring and backstopping visit at Cotton Farmer Field Schools in
Lamu West District, Kenya.
In Mozambique, besides monthly mentoring visits by IAM technical staff, joint mentoring
and backstopping visits were conducted by the project team/master trainers from CABI, IAM
and SANAM at least once during each cropping season. Given that the majority of the FFS
facilitators (extension officers from the private companies) in Mozambique were not used to
FFS participatory techniques and tools, a hands-on refresher ToT on FFS methodologies and
cotton ICM was conducted from 6th – 12th June 2011 by CABI’s Farmer Participatory
Training and Research Expert with support from IAM’s National Project Coordinator in
Nampula. The 38 participants included leading farmers, representatives from four local
farmer associations and the National Forum of Cotton producers (FONPA). During the ToT
the topic on “Quality control and post-harvest handling” was conducted by a Cotton Fibre
Classing technician from IAM-Beira. In addition, due to the expressed need for an in-depth
training on pest management by the FFS facilitators in Mozambique, a practical ToT on IPM
was conducted as indicated in Section 3.1.2.2.
22
Mentoring and technical back-stopping visit: ICM Plot (left) and non-ICM plot at a Farmer Field
School in Monapo district, Nampula, Mozambique.
3.1.2.7 Dissemination of best ICM strategy through farmer field days and mass media
In Kenya eight local field days were held in March 2011 at various FFSs sites; five in
Kathonzweni, two in Tharaka South and one in Kitui Central Districts. More than 600
farmers (58% female) participated. A regional field day was conducted in June 2011 in
Kathonzweni District (Kitise location), which was attended by a wide range of stakeholders
including representatives from: Kitise Rural Development, World Vision, Catholic Relief
Services, Farm Concern International, Makueni Ginneries, Syngenta, Twiga Chemical
Industries Ltd., Farmer groups and Athiani cotton FFS. The main technologies demonstrated
during the field days included early planting and response of the cotton crop to application of
fertiliser. In addition, local field days (one each) were conducted in Baringo North, Tana
Delta and Lamu West Districts. Two newspaper articles to showcase the project’s activities
were published in the Business Daily (7th February 2011) and the Financial Journal (8th
February 2011) in Kenya.
Field day at FFS site in Kitui Central District, Kenya
In Mozambique, the project results were disseminated through a revised manual on integrated
crop and pest management in cotton, a pocket handbook for the identification of cotton pests,
and posters on integrated pest management in cotton (Section 3.3). All the cotton companies
in Mozambique have access to the ICM materials, and have printed copies and distributed
them through their own extension networks to farmers, thus reaching many farmers. By the
end of the project, IAM was developing a radio programme with a focus on cotton production
for broadcasting by local radio stations in all cotton priority districts. The programme covers
23
ICM issues including IPM, conservation agriculture and good agricultural practices (GAP) in
cotton.
3.1.3 Stakeholder Linkages for Sustaining ICM (Component 3)
Implementation of project activities in ccomponent 3 was linked to ongoing initiatives for
development of the cotton subsector led by the national cotton bodies CODA and IAM. This
was done to ensure that the activities were in line with government policies and aligned to
national and regional priorities. The key issues addressed in this component were supply of
inputs such as quality seeds, and credit for cotton farmers. The project aimed to strengthen
these areas by facilitating linkages between key stakeholders in the cotton value chain.
This component had three indicators: four stakeholder awareness workshops planned and
held (Indicator 3.1), stakeholder linkages established (Indicator 3.2) and lessons learned and
best practices widely circulated (Indicator 3.3). All the indicators were fully met as discussed
in the sections below.
3.1.3.1 Conduct stakeholder mapping of value chain and produce plan for workshop
The PIA in Kenya (KARI), in consultation with the national cotton body (CODA), identified
stakeholder groups at the various stages in the cotton value chain i.e. technology
development, input suppliers, production, collection and transportation, processing and
distribution. The PIA in Mozambique (IAM), which is also the national cotton body,
identified similar stakeholder categories. The PIAs advised that to avoid duplication of
meetings, the schedule of stakeholder workshops in this component should be aligned to the
scheduled annual planning workshops and local stakeholder workshops, chaired by the
national cotton bodies in the respective countries (Section 3.1.3.2).
The first stakeholder workshop was therefore the project inception workshop held in
Mozambique in November 2009 (Section 3.1.5.1), to which representatives from Kenya and
Mozambique were invited. However, as it was not possible to invite many representatives
from Kenya, a local stakeholder workshop was held in March 2010 at the Government
Training Institute (GTI) in Embu, Kenya where all the stakeholder groups were represented.
Official opening and participants at the Cotton Stakeholder Workshop and Technical Planning Meeting, at the
Government Training Institute in Embu, Kenya
A more detailed mapping of stakeholders and their different roles in the cotton value chain
was undertaken during a workshop hosted by CODA and KARI. The key actors, their
constraints and expected interventions are shown below.
24
Production
Input Suppliers
Technology Development
Category
Actors
 KIRDI
 KARI
 Universities
 KEBS
 Exporters
 KEPHIS
 International Research
Stations
 CODA
 MoA
 Tertiary Institutions
 Ginners
 Textile Mills
 Seed Companies
Constraints
 Pests and diseases
 Limited funding
 High Cost of inputs and
equipment
 Limited Research
 Lack of Modern research
Infrastructure
 Limited Competent Research
capacity
 Weak linkages among actors
 Inadequate Infrastructure
 Weak theme specific research
teams
 Seed Suppliers
 Exporters/Importers
 Ginners
 Textile Millers
 KARI
 CODA
 Agro-Chem Companies
 NGOs
 KEPHIS
 KEBS
 PCPB
 Financial Institutions
 GoK
 Farmer
 MoA
 CODA
 NGOs
 NARS
 Ginners
 International
Agricultural Research
Institutions
 Financial Institutions
 GoK
 Agro-chemical
companies
 Universities
 KEPHIS
 PCPB
 Inadequate Enforcement of
available policies
 Inadequate information on
inputs by suppliers/vendors
 High Importation costs
 Weak linkage among the
actors
 Lack of certified seed
production system
Interventions
 Development of
tolerant/resistant varieties and
other appropriate management
practices
 GoK and development partners
to increase research funding
 Availability of organic inputs
 Development of appropriate
demand driven technologies
 Establishment of stakeholders
research fund
 Recruitment of
breeders/Mentorship
programmes/ NARS policy
 GoK subsidizes on inputs
 Acquire and adopt modern
production technologies
 Develop farmer friendly policies
 Public dissemination of
information on regulations and
protocols
 Subsidizing by the Govt.
 Establishment of a seed
production system
 Capacity build farmer
organizations
 Inadequate quality seeds
 Counterfeit pesticides / lack
of appropriate knowledge and
skills on pesticides and their
application
 High cost of inputs
 Pests and diseases
 Limited irrigation
infrastructure
 Weak farmer organizations
 Lack of knowledge on
pollination
 Limited knowledge on cotton
production
 Inadequate extension services
 Enhancement of Private/public
partnership in breeding.
 Training/recruitment of more
breeders in cotton industry.
 Enforcement by Regulatory
bodies
 Contract Farming
 Development of appropriate
agronomic packages/farming
systems
 Capacity build farmers on
irrigation and moisture
management
 Work out modalities for funding
production
25
Distribution
Processing
Collection/
Transportation
Category
Actors
 Farmer Groups
 NGOs
 CODA
 Ginners
 Buyers
 Private Transporters
Constraints
 Poor road infrastructure
within the production areas
 Inadequate buying/storage
centres
 Inappropriate packaging
 Unavailability of localized
standards for postharvest
handling
 High cost of packaging
materials
 Ginners
 Spinners
 Weavers
 CODA
 KIRDI
 KEBS
 MoA
 Universities
 Apparel Manufacturers
 Seed Oil and animal
feed manufacturers
 EPZA
 GoK
 KAM/KAMEA
 Low volumes of raw
materials
 Inadequate knowledge on
cottage processing
 Lack of appropriate
equipment
 High cost of energy for
processing
 Inadequate finances
 Importation of cheap raw
materials and finished
products
 Restrictions of sale of
apparels from EPZ to EAC
market
 Farmer Groups
 NGOs
 CODA
 KEBS
 Exporters
 Merchants
 Processors
 Transporters
 Wholesalers
 Insurance companies
 Financial institutions
 GOK
 Poor road/railway
infrastructure within the
production and processing
areas
 Inadequate storage facilities
 Inappropriate transportation
packaging
 Lack of public code for good
transportation practices
 Lack of adherence to set
standards for packaging and
handling
26
Interventions
 Lobby government for
allocation of resources to road
infrastructure
 Enforcement of use of
appropriate buying/storage
centres.
 Capacity building in postharvest handling and
enforcement on use of good
packaging practices
 Development and
mainstreaming of localized
postharvest standards
 Explore cheaper alternative
packaging materials
 Promote use of modern
technologies for increased
production e.g. transgenic cotton
 Exploit the local institutional
and human capacity
 Review of curriculums for
training at all levels of the value
chain
 Exploit the local alternative
energy sources
 Design appropriate financing
packages
 Enforce government policy
 Lobby GoK to spearhead review
of restrictive legislation on EAC
 Lobby GoK to lower energy
tariffs for the sector
 Build capacity to exploit the
preferential market access
arrangements
 Allocation of resources and
prioritization
 Investment in storage facilities
 Enforcement of policy on
transport facilities.
 Capacity building in handling
and enforcement on use of good
transportation packaging
practices
 Development and
mainstreaming of code for
transportation
Consumption
Marketing
Category
Actors
 Wholesalers
 Retailers
 Supermarkets
 Processors
 Packaging companies
 CODA
 Ginners
 GOK
 EPC
 KEBS
 EPZA
 Farmer organisations
Constraints
 Poorly organized marketing
structure.
 Low quality produce.
 Low quantities
 High cost of products
 lack of transparency across
the chain
 monopolistic practices
 inadequate enforcement of
regulations on standards and
taxation
Interventions
 Exploit the new government
policy on market development
 Capacity build along the value
chain
 Facilitate production for other
potential areas through irrigation
 attract new investment in the
sector
 enforcement of trade regulations
and marketing standards
 GOK
 Institutions
 Households
 Pharmaceutical
industries
 Exporters
 Limited knowledge on
product range and availability
 Limited of awareness on
value addition opportunities
 Low consumer preference for
locally manufactured
products
 Low purchasing power
 inadequate availability of the
products
 Capacity building on awareness
of available products.
 Disseminate knowledge on
utilization and value addition.
 Product diversification
 import raw materials to
supplement local production
 exploit available land to produce
sufficient raw materials
Source: Kenya Agricultural Research Institute
In Mozambique, cotton production and marketing is undertaken through the concession
system as per Cabinet of Ministers Decree No. 8 and Ministerial Order No. 91/94. Under this
arrangement, private companies are obliged to provide inputs and technical assistance to
cotton farmers, and in return, the company has exclusive right to procure all cotton produced
in the area of concession. The ginners are represented by the Cotton Association of
Mozambique (AAM), whereas the famers are represented by the National Forum for Cotton
Producers (FONPA). The National Cotton Institute (IAM) has the key mandate of enforcing
concessionaire rights, mediating conflicts and setting minimum prices in consultation with
AAM and FONPA.
3.1.3.2 Conduct a workshop annually to plan /review pilot schemes in each country
The existing systems for delivery of inputs and technical support in Kenya and Mozambique
were discussed during the stakeholder workshops under Component 1 both in Kenya and
Mozambique (see Section 3.1.2). The meetings included a fibre crops sub-sector analysis and
priority setting stakeholders’ workshop held on 26th to 28th April 2011 in Kenya. In
Mozambique, to maintain continuous dialogue and to promote consensus among stakeholders
in Mozambique, existing platforms were used for dialogue and coordination, at which issues
of common concern were discussed. Such fora included the Cotton Technical Annual
Meeting (Reunião Tecnica Anual do Algodão) and IAM Technical Meeting (Retiro tecnico
do IAM) held in March and June every year.
3.1.3.3 Implement pilot schemes
A major challenge for cotton farmers is availability of quality cotton seed for planting. To
enhance local cotton seed multiplication and supply to farmers in Kenya, in the 2011/12
cropping season KARI breeders provided Kenya Seed Company with white label seed (KSA
81M) for multiplication. During the project, the Kenyan Government supplied cotton farmers
27
in five of the pilot project districts with good quality seed (4th generation HART 89M),
though this is not certified through CODA. In the 2011/12 season, the total seed supplied by
CODA to farmers in the different districts was: Kathonzweni - 37 tons, Kitui Central - 18
tons, Tharaka -12 tons, Lamu West - 114 tons and Kipini - 15 tons. The cost of these seeds
was US$ 92,800. Some farmers in Baringo North District received some inputs from Salawa
Ginneries, whereas some farmers near the project sites in Lamu West District received credit
support for purchase of inputs from Equity Bank. Through CODA, the project has also been
working closely with other partners such as the Kenya Gatsby Trust, which is implementing
two pilot schemes to support adoption of ICM packages (spray management, etc.) and market
access (Annex 6). The key approach is to promote a contract farming arrangement between
farmers and ginneries in their respective areas.
In Mozambique, activities were aligned with the ongoing initiatives of the Cotton Value
Chain Revival Sub-programme (CVCRS), which focuses on the improvement of seed quality,
use of improved farm practices, better access to inputs and credit, establishment of risk
management mechanisms and institutional and infrastructural development. Under the
framework of the CVCRS, IAM and input suppliers are implementing an alternative input
supply mechanism called "Local Input Providers Programme" to address the inadequate
access to inputs and improve the input supply system in terms of timeliness, quantity and
quality. The mechanism is being implemented in all priority districts including those where
the current project worked.
In order to demonstrate the value of using quality seed, the project supplied a range of inputs:

Pesticides, Micron ULV sprayers and batteries, and protective clothing

Treated cotton seeds (basic) from CIMSAN (var Albar SZ) for OLAM Ribaue
concession and treated seed (imported from Zimbabwe) through the cotton companies
e.g. SANAM

Maize (PAN 67) and Beans (Feijao Nhemba) for strip intercropping.
By 2012, AgriFocus Lda was the only supplier of cotton pesticides and other inputs
(inorganic fertilisers, sprayers and protection equipment). However, through the stakeholder
forums chaired by IAM the project initiated stakeholder dialogue, and more companies are
now supplying inputs, including BIOCHEM Lda, AgroGlobal, and Tecap.
To respond to the shortage of certified cotton seed in the country in the long term, a draft
Mozambique Cotton Law (Regulamento para Cultura do Algodão) would make it mandatory
for cotton companies to supply certified seed to the farmers. The draft was presented and
discussed during the Cotton Stakeholders’ Meeting in Pemba, Cabo Delgado Province in
October 2012. In addition, a cotton seed production system has been established. For
example, IAM and Mocotex Cotton Company based in Mocuba, Zambézia Province have
already signed a MoU to produce and supply certified cotton seed to the concessionaires
companies. Mocotex is producing 500 tonnes of certified cotton seed per year. Some of the
seed is delinted and treated and further distributed across the country.
After a series of consultations with stakeholders such as Food and Agricultural Organization
(FAO), IIAM, INAM, the World Bank and IFC among other actors in the cotton value chain,
IAM launched a pilot Agricultural Insurance Programme for Cotton. The programme initially
covered total 38,700 ha, benefiting 6,000 farmers from Lalaua (OLAM) and Monapo
(SANAM) Districts, in Nampula Province. The programme involves two iinsurance
28
companies, namely EMOSE and Hollard Insurance. From 2012, Mozambique started the
implementation of the Better Cotton System, with the aim of driving the country’s cotton
production towards sustainability. After meetings and talks with the cotton sector
stakeholders in the country, the Government decided to embed the Better Cotton System
within the legislation, to ensure that all cotton producing farmers in the country will benefit
from it. So far five (SANAM, OLAM-Ribaue, OLAM AVZ, OLAM Morrumbala and SUN
JFS) out of the 14 Mozambican cotton companies have joined the program.
3.1.3.4 Final stakeholder learning workshop - sharing lessons learned on pilot schemes
The final workshop was held in Mozambique on 19th December 2013. Lesson learning was
linked to the other dissemination activities described in Section 3.3, in which lessons from
the pilot schemes were shared through different channels and fora.
3.1.4 Impact of ICM Adoption Evaluated (Component 4)
Under Component 4, a baseline survey was conducted at the start of the project through
Focus Group Discussion (FGD) and Key Informant Interviews (KII), using questionnaires
and checklists, to establish the pre-adoption socio-economic situation and production
practices in the Project areas in both Kenya and Mozambique.
This component had only one indicator: Data on benefits of ICM, available by end of project
(Indicator 4.1). In this context, a ‘before and after’ analysis was carried out, and a
comparison made between “adopters” and “non-adopters” of the ICM package, to measure
impact of the technologies and their contribution to farmers’ income and livelihoods in
Mozambique. There were challenges in undertaking an impact evaluation in Kenya due to
budget limitations, following the limited approved budget by the fund for the final year.
3.1.4.1 Conduct Baseline Survey (linked to activity 1.3) to establish pre-adoption socioeconomic situation and production practices
This activity was executed simultaneously with the survey described in Section 3.1.1.1 in
both the pilot and comparison (control) Districts in Kenya and Mozambique.
3.1.4.2 Conduct impact assessment (before and after analysis)
Following the implementation of capacity building activities for the farmers, an impact
assessment was conducted in 2013 to measure the impact of the ICM technologies and their
contribution to farmers' income and livelihoods. The assessment was to establish how
effectively these practices are being used and how many of the farmers whose capacity was
improved are using the practices. This component is further discussed in Section 3.2.
3.1.4.3 Synthesise and analyse the findings
The key highlights from the baseline survey are articulated in Section 3.1.1 and details of the
analysis form the impact assessment study presented in Section 3.2
3.1.4.4 Disseminate the findings of the impact assessment
The results of the baseline surveys and the impact assessment study were disseminated using
the pathways described in Section 3.3.
29
3.1.5 Project Co-ordination and Management (Component 5)
Coordination and management of the project was dealt with under Component 5, which had
only one indicator: project outputs delivered as per the log-frame (Indicator 5.1). Overall the
coordination and management of the project during the implementation period went as
planned and the expected outputs delivered.
However, there were some changes in the project coordination team in Mozambique during
the project period, which in some cases delayed implementation of some activities. In
February 2011 Ms Rosa Meque was appointed as the new project accountant, on an interim
basis, pending recovery of Mr João Cossa, who was on a long sick leave. To ensure a smooth
transition the PEA conducted a hands-on training (8th to 9th March 2011) for the new project
accountant to acquaint her with the CFC financial and administration procedures. Mr Cossa
resumed duties in June 2011 and continued with his role intermittently until his demise in
February 2013. Subsequently Mr. Samuel Guambe was appointed as the new project
accountant for Mozambique. In addition, in May 2012 Ms. Licínia Cossa was replaced as
Coordinator of the project by Mr. Hélder de Sousa, Head of the Department for Small
Farmers Assistance in the Mozambique Institute for Cotton. Again to ensure continuity and a
smooth transition, the PEA provided a hands-on training (31st August 2012) to the new
project coordinator and the accountant, who was then working in an interim capacity. There
were no changes in the coordination team from the PIA in Kenya throughout the project
period. In the PEA, Mr Alphonce Werah took over from Mr Tom Owaga as the Project
Accountant in May 2011.
Specific project management and coordination activities are described below, while the
lessons learned are described in Section IV.
3.1.5.1 Support organization of an inception workshop and support establishment of CFC
administrative and accounting procedures and train local counterparts in project
procedures
A project Inception workshop was conducted in Maputo, Mozambique from 24th to 26th
November 2009) through pre-financing by the PEA. This marked the official launch of the
project, where both the project implementation teams from Kenya and Mozambique met to
discuss and agree on Year 1 work plans and budgets (December 2009 – November 2010).
During the workshop, the PEA conducted a general training for the PIAs on CFC financial
and administrative procedures. The training was aimed at acquainting the PIAs with the
Fund’s requirements and best practices in technical and financial operations to ensure the
success of the project. The PEA also provided additional specific financial training to the
PIAs as needed during implementation of the project, as described in Section 5.1.2. By March
2010 the CFC administrative and financial procedures had been established, including
opening of dedicated projects bank accounts (United States Dollar and local currency) and
appointment of national coordinators in Kenya and Mozambique. This was followed by
signing of project sub-contracts between the PEA and the PIAs. The PEA also signed a joint
contract with the designated commodity Supervisory Body (ICAC) and the Fund (CFC).
30
Participants at the project Inception Worksop in Maputo, Mozambique,
24th to 26th November 2009
3.1.5.2 Advise on operational procedures and initiate consultancies where necessary
In addition to the general training on financial and administrative procedures provided by the
PEA to the PIAs at the project inception workshop, and various trainings offered to new
project coordination team members in Mozambique (see Section 5.1.1), the PEA conducted
hands-on in-country training on the preparation of financial claims. This was provided to the
project accountants in both Kenya (April 2010) and Mozambique (May 2010). Throughout
the project, the PEA supported the PIAs’ project accountants in preparing financial
claims/bimonthly cash flow reconciliations. The PEA also assisted with the selection of audit
firms and the annual financial audits. Project staff were given technical backstopping where
they were needed support in implementing the project activities, especially on socioeconomics, training of trainers and implementation of the Farmer Field Schools. Advice was
also communicated through email and telephone communication, monitoring visits, and
meetings such as annual project planning meetings.
3.1.5.3 Assist PIAs and ICAC to prepare necessary documentation, including budgets and
work plans
During the project period, the PEA assisted the PIAs to prepare their respective annual work
plans and budgets and progress reports in accordance with the CFC formats. The draft work
plans were discussed during annual planning meetings organised by the PEA in collaboration
with the PIA in the host country. Annual meetings alternated between Mozambique and
Kenya:
 November 2009: Mozambique
 December 2010: Kenya
 December 2011: Mozambique
 December 2012: Kenya
 December 2013: Mozambique
31
All work plans and budgets and reports were revised accordingly after the planning
workshops, based on consultations with ICAC and CFC, before final submission and
endorsement by CFC.
3.1.5.4 Liaise between project donors and implementers and arrange exchange visits
The PEA maintained contact with CFC, ICAC and PIAs through e-mail, phone and face to
face meetings, and organised visits in consultation with the host country. Field visits were
organised as part of the annual planning meetings, hosted in Kenya and Mozambique
alternately, where the visiting project team members and other stakeholders in attendance had
an opportunity to interact, learn and share ideas/experiences. Through support from Dr Rafiq
Chaudhry from ICAC, the project was able to link up and learn from another CFC-funded
project in Kenya and Mozambique, supporting national cotton classification laboratories to
bring them in line with instrumental classification standards (CFCI/ICAC/44).
Dr Rafiq Chaudhry (left) and project team (right) visiting the cotton classing room being renovated
through CFC-funded project CFCI/ICAC/44 at the Cotton Development Authority site hosted by
KARI- Kabete, Nairobi, Kenya, in August and December 2012.
The project coordination team also initiated and maintained contact with other national,
regional and pan-African cotton initiatives, enabling participation in and co-hosting of
meetings. Effective links were maintained with the East & Southern Africa component of the
EU All ACP Agricultural Commodities Programme (AAACP), Common Market for East and
Southern Africa (COMESA), Southern African Development Community (SADC), East
African Community (EAC), African Cotton and Textile Industries Federation (ACTIF), and
Cos-Cotton, the steering and monitoring committee of the EU-Africa Cotton partnership.
3.1.5.5 Monitor project progress and report on inputs (disbursements), activities undertaken
and outputs achieved
The PEA together with the PIAs jointly conducted monitoring visits to assess both the
technical and financial aspects of project implementation. As indicated in Section 3.1.5.2, the
PEA project accountant monitored and assisted the PIAs in preparing and submitting
financial claims on completed activities, and in implementing audits.
The PEA also facilitated joint monitoring visits by ICAC (Dr Rafiq Chaudhry) to the project
sites in Kenya and Mozambique in November 2010; by CFC (Ambassador Ali Mchumo) to
Nampula, Mozambique in August 2011; by CABI Senior Managers (Dr Julie Flood and Ms
Patricia Neenan) in Eastern Kenya in March 2011 and May 2012.
32
The PEA and the PIAs were jointly involved during the Mid-Term Review of the project
conducted in Kenya and Mozambique by consultants from 10th to 22nd September 2012. The
evaluation team was accompanied by an observer, Mr. Abdelatif Ahmed Mohamed Ijaimi,
the Chairman of the Consultative Committee of CFC at that time.
3.1.5.6 Assist PIAs and partners with planning and co-ordination of activities aimed at
providing uptake pathways for outputs
The farmer participatory and training expert from the PEA directly supported the training of
trainers on farmer participatory approaches for promoting the uptake of ICM technologies by
farmers. The PEA also participated and assisted in planning of dissemination events such as
field days and stakeholder meetings mentioned in Section 3.1.2.
3.1.5.7 Prepare regular progress reports, mid-term evaluation report, annual accounts, audits
and project completion report.
The PEA, in collaboration with the PIAs, prepared and submitted progress and annual
technical reports, annual audit reports, and this project completion report. The PEA also
contributed to the writing of the mid-term review report as required.
3.2 Project Results Achieved
The immediate results of the project have been reported in the previous section. However, a
study was also conducted to assess the results in terms of changes and improvements to
farmer practices, cotton production and productivity, and income at the farm level. The
assessment involved a comparison of adopters of the ICM practices and non FFS farmers in
the same project area, and also with famers in other non-project areas. The study was
undertaken in Nampula Province, Mozambique where the project worked.
The following sections summarise the results of Annex 9
3.2.1 Extent of use/effect of integrated crop management practices
Participating farmers and other stakeholders in all the districts reported that the capacity
building through training in ICM enabled the cotton growers to change their production
practices. A general trend noted was the increased use of IPM practices, and reduction in the
use of pesticides by farmers who participated in the trainings. There was an integration of
good farming practices by some of the participating farmers in the areas under the project.
This demonstrates willingness by the cotton growers to learn and practice new cotton
production skills to improve cotton productivity. It was found that given the appropriate
support, cotton growers can change their production practices and improve productivity.
The cotton growers noted that their knowledge and skills had increased on a range of
production activities. These included sowing and the need for correct spacing; timely
weeding to limit weed growth which also discourages infestation by insect pests; using traps
to attract pests for monitoring; scouting for pests to determine whether spraying is actually
needed. All these changes were reported to be associated with an increase in cotton yields and
hence, the amount of seed cotton farmers sold to the cotton companies.
33
3.2.2 Cotton production and productivity
The land allocated to cotton production has increased in more than half of the project areas
after the ICM initiatives. In two districts, Lalaua and Ribaué, there has been a decline in area
devoted to cotton after the ICM initiatives (Figure 3). Lalaua and Ribaué joined the ICM
initiatives much later and it is possible that the effects of ICM practices have not yet been
appreciated by the farming community to encourage more cotton growers to devote land to
cotton production. A similar trend is observed in the control districts where there has been a
decline in area under cotton in Murrupula District while there is no change in area under
cotton in Muecate District.
Two other issues were also identified during the project. Firstly, cotton productivity is
affected by lack of the necessary production skills and support, meaning that more technical
and material support is required to facilitate cotton production. In the second instance, it is
possible to infer that if measures are not taken to help in the production practices of cotton
then the area under cotton production may continue decreasing thereby reducing the
competitiveness of cotton. The second assertion is based on the decline in area under cotton
for the control districts and the participating district that has not been adequately exposed to
the ICM practices and other support.
Figure 3. Land under cotton production in the project and control (Murupula and Muecate) districts
In most of the districts, there were increases in the yield of cotton after the adoption of the
ICM practices (Table 6), although it is noted that the yield on farms not participating in the
project also increased, but generally not to the same extent. This could be due to spill over
effects from the project area, or to the related efforts and initiatives to improve cotton
production. However, in the two districts not participating in the project, yields fell between
the baseline and final assessments.
34
Table 6. Cotton production in the different districts on the farmers’ own fields (kg/ha.)
Cotton
District
company
Before
the
project
(a)
After
the
project
(b)
SANAM Mecuburi
Meconta
Monapo
Muecate*
OLAM Lalaua
Ribaue
Murupula*
474.8
494.3
595.9
428.5
510.8
432.2
411.9
752.4
557.5
674.5
455.9
641.7
554.3
510.8
Differences
(Yield after
ICM less
before ICM)
(c)
277.6
63.2
78.6
27.4
130.9
122.1
98.9
Difference-indifferences
(ICM less
Comparison)
(d)
250.2
35.8
51.2
32
23.2
-
%
Change
in yield
(e)
(d/a)*100
52.7
7.2
8.6
6.3
5.4
-
Note: 1. *=Comparison district
2. After ICM for the comparison districts refers to the period after the project districts had completed
implementing the ICM practices
Thus although yields were higher on participating farms, they were not significantly different
(F1, 145=0.03, p>0.05) from those on the non-participating farms.
The cotton growers with improved knowledge of ICM practices (through the project)
demonstrated good production practices and post-harvest handling of the cotton. They also
reported improved communication amongst themselves in comparison with other cotton
growers. This interaction may help the cotton growers to negotiate more effectively with the
cotton companies that serve the areas where they undertake cotton production. Cotton was
packed more effectively in the fields of the ICM farmers, although the sorting and grading
did not show major differences between the ICM adopters and the non-ICM adopters. ICM
farmers reported increased capacity to source for information that they needed.
At the demonstration plots in farmer field schools, production in all cases was much higher in
the ICM plots than in the plots under conventional farmer practices (p<0.05, Table 7). Yields
in the demonstration plots were also higher than those reported by farmers in the survey,
suggesting that there may still be scope for further improving on-farm ICM practices.
Table 7. Cotton production in the farmer field schools (kg/ha)
ICM Plots
Name of cotton company
SANAM
OLAM
District
Mecuburi
Meconta
Monapo
Lalaua
Ribaue
Season 1
(2011/12)
869.2
643.0
823.3
772.7
800.0
35
Season 2
(2012/13)
746.8
720.0
711.0
784.1
888.8
Conventional plots
(Farmer practice)
Season 1
Season 2
(2011/12)
(2012/13)
441.4
602.0
437.0
388.0
398.0
635.5
530.0
627.3
497.6
550.0
3.2.3 Pesticide use in the project area
All the pesticides used were provided by the cotton companies in the project area. The
companies directed the farmers on the purposes and methods of using the pesticides. The
main pesticides used were insecticides such as Acetamiprid (Volamiprid 22.2% SL), Lambda
– Cyhalothrin 60g/l + Acetamiprid 40g/l (Zakanaka Top 10% EC), Lambda – cyhalothrin
60g/l (Zakanaka K 6% EC) and Lamba – cyhalothrin 48g/l + Profenofos (Zakanaka Pro
64.8% EC). Focus group discussions revealed that the ICM farmers now spend less on
pesticides as the frequency of use is relatively lower than among non-ICM cotton growers.
The reduced frequency may be due to the timely control made possible through the use of
agro-ecological system analysis. Pest and disease incidence levels were reported to have
declined despite the reduction in the use of pesticides. However, data from the farms
indicated that pesticide expenditure had reduced in 3 of the 5 districts, but had increased in 2
districts (Table 8). Highest expenditure on pesticides was in one of the comparison nonproject districts.
Table 8. Expenditures (money spent) on pesticides (Mt/ha.)
Name of District
cotton
company
Before After
the
the
project project
(a)
(b)
SANAM Mecuburi
Meconta
Monapo
Muecate*
OLAM
Lalaua
Ribaue
Murupula*
438.5
435.3
462.4
350.7
511.4
545.8
362.2
314.4
416.5
301.8
366
330.6
385.8
459.6
Difference
(Expenditure
after ICM less
before ICM)
(c)
-124.1
-18.8
-160.6
15.3
-180.8
-160
97.4
Difference-indifferences
(ICM less
Comparison)
(d)
-139.4
-34.1
-175.9
-278.2
-257.4
-
% Change
in
Expenditure
(e)
(d/a)*100
-31.8
-7.8
-38.0
-54.4
-47.2
-
Note: 1. *=Comparison district
2. After ICM for the comparison districts refers to the period after the project districts had completed
implementing the ICM practices
3. Mt = New Mozambican meticais (currency)
One of the factors constraining more efficient use of pesticides reported by ICM adopters was
difficulty in accessing and using them at the right time. The sprayers and the batteries for the
sprayers were not readily available, as sprayers are shared by many farmers. This problem
was addressed in the field schools by reducing the number of farmers sharing a sprayer.
Farmers suggested that the Concession Companies could provide more sprayers and
accessories, but farmers could also pool resources of their own to purchase the equipment.
3.2.4 Contributions of ICM to farmers’ income
The returns to cotton production demonstrated an improvement for the cotton growers that
participated in the ICM activities in all five districts (Table 9).
36
Table 9. Net income per hectare from cotton production (Meticais)
Cotton
District
company
Before
the
project
(a)
SANAM Meconta
Mecuburi
Monapo
Muecate*
OLAM
Lalaua
Ribaue
Murupula*
6,281.9
4,246.5
4,000.5
3,648.4
5,538.0
5,121.2
3,500.6
After
the
project
(b)
8,831.8
5,980.6
4,390.2
3,946.5
5,872.3
5,430.5
3,698.4
Difference
(Income after
ICM less
before ICM)
(c)
2,549.9
1,734.1
389.7
298.1
334.3
309.3
197.8
Difference-indifferences
(ICM less
Comparison)
(d)
2,251.8
1,436.0
91.6
136.5
111.5
-
%
Change in
income
(e)
(d/a)*100
35.8
33.8
2.3
2.5
2.2
-
Note: 1. *=Comparison district
2. After ICM for the comparison districts refers to the period after the project districts had completed
implementing the ICM practices
The results indicate that use of the ICM practices is likely to increase net incomes from
cotton production which in turn suggests that the cotton growers need to be encouraged to use
the ICM practices. Net cotton income from the farmers in the comparison district was lower
than that of the project districts for both concessions.
Improved cotton income received by the farmers that have adopted the ICM practices can be
used to purchase household requirements and thereby improve the livelihoods of the cotton
growers. This is crucial given that the cotton growers have limited alternative income
generating activities.
3.3 Dissemination of Project Results
Dissemination of project results was built into the other project activities (Section 3.1).
Different information delivery pathways were used to convey or deliver information to
various target audiences. These included print (newsletter and newspaper) and mass media
e.g. radio and television, who were invited to project events such as field days, monitoring
visits and stakeholder meetings. The annual review and planning workshops were essential in
reaching a wide range of stakeholders.
Science journalists from WREN media accompanied the PEA and the PIA during a
monitoring visit (May 2012) to FFSs in Eastern Kenya. During the visit the journalists
interviewed participating farmers and prepared radio and video clips for the event. The clips
were shared using social media (http://www.youtube.com/watch?v=5K3nQ43aq8k). In
addition, on-farm demonstrations and field days organised held at FFS sites, exhibitions were
used to showcase the best management practices for production cotton.
The project also used national, regional and international fora to disseminate the project
outputs, including:
 Africa Green Revolution Forum 2012, Tanzania
 Meeting of the Southern and Eastern African Cotton forum (SEACF), Zambia and Kenya
37
 5th World Cotton Research Conference, India
 Eastern African Regional Cotton, Textile and Apparel Stakeholders Meeting, Uganda
 Common Market for Eastern and Southern Africa, Cotton to Clothing Value Chain
Stakeholders’ Review meeting, Kenya
 Fibre Crops Agricultural Product Value Chains (APVC) Analysis Workshop, Kenya
 Cotton Technical Annual Meeting (Reunião Tecnica Anual do Algodão) and IAM
Technical Meeting, Mozambique
Dissemination materials and products produced by the project include:
 Posters/Fliers/Manuals:
o Improving cotton production in East Africa – CABI Project flier
o Programa de Maneio integrado de Pragas do Algodão - poster
o Manual Sobre o Maneio Integrado da Cultura do Algodão) – Manual for extension
workers on Integrated Pest Management in Mozambique
o Sobre o Maneio Integrado da Cultura do Algodão – pocket handbook for cotton
farmers
 Newsletter/Newspaper articles:
o Cottoning on to ICM. In: CABI in Africa Newsletter 2013/14 edition. pp 4.
o Business Daily (7th February 2011), Kenya
o Financial Journal (8th February 2011), Kenya
o DPA communication - Noticias newspaper (September 2010), Mozambique.
 Papers/oral presentations/exhibitions:
o CABI (2012). Improving cotton production in East Africa Africa. Exhibition at
the Africa Green Revolution Forum 2012, Ngurdoto Mountain Lodge, Arusha,
Tanzania, 26 – 28 September 2012.
o L Cossa, D Karanja, R Musebe and M Kimani (2012). Experience of Integrated
Crop Management in Cotton Production Systems Disseminated in Mozambique
through the Project “Improving Cotton Production Efficiency in Small-scale
Farming Systems in East Africa (Kenya and Mozambique) through Better Vertical
Integration of the Supply Chain – CFC/ICAC/37”. 11th Meeting of the Southern
and Eastern African Cotton forum (SEACF), 27th -29th August 2012, Nyeri,
Kenya.
o D Karanja, R Musebe, W Gitonga, A Mungai, J Macharia, A Gikandi, L Muthoni,
L Wasilwa and M Kimani (2012). Enhancing smallholder farmers’ decision
making in pest management on cotton in Kenya. 11th Meeting of the Southern and
Eastern African Cotton forum (SEACF), 27th -29th August 2012, Nyeri, Kenya.
o Musebe, R, Karanja, D, Gitonga, W, Cossa, L, Mungai, A, Macharia, J, Mwai,
AG, Gikandi, A, Muthoni, L and Kimani, M. (2011). Comparative analysis of
production practices and post-harvest handling of cotton by smallholder farmers in
Kenya and Mozambique. Abstract of Paper to be presented at The 5th World
Cotton Research Conference, November 7-11, 2011, Mumbai, India.
o Musebe, R, Karanja, D, Gitonga, W, Cossa, L, Mungai, A, Macharia, J, Mwai,
AG, Gikandi, A, Muthoni, L and Kimani, M. (2011). Comparative analysis of
production practices and post-harvest handling of cotton by smallholder farmers in
Kenya and Mozambique. Oral presentation at The 5th World Cotton Research
Conference, November 7-11, 2011, Mumbai, India.
o D Karanja, W Gitonga, J Macharia, A Mungai, M Kimani, R Musebe, A. Muriithi
(2011). Special initiative to boost cotton production in Kenya. Eastern African
Regional Cotton, Textile and Apparel Stakeholders Meeting, 30th – 31st August
2011, Africana Hotel, Kampala, Uganda.
38
o D Karanja, W Gitonga, J Macharia, A Mungai, M Kimani, R Musebe, L. Cossa
(2011). Improving cotton production efficiency in small-scale farming systems in
Kenya and Mozambique. Common Market for Eastern and Southern Africa,
Cotton to Clothing Value Chain Stakeholders’ Review meeting, 29th – 30th July
2011, Hilton Hotel, Nairobi, Kenya.
o D Karanja, W Gitonga, J Macharia, A Mungai, M Kimani, R Musebe (2011).
Improving cotton production efficiency in small-scale farming systems in Kenya
and Mozambique. Pan-African Cotton Meeting, A high-level Multi-stakeholder
Conference, 27th - 29th June 2011, Cotonou, Benin.
o D Karanja, W Gitonga, J Macharia, A Mungai, M Kimani, R Musebe (2011).
Improving cotton production efficiency in small-scale farming systems in Kenya
and Mozambique. Fibre Crops Agricultural Product Value Chains (APVC)
Analysis Workshop, 26th - 28th April 2011, Egerton University Njoro, Kenya.
o Daniel Karanja, Marsden Momanyi, Kimani Chege (2011). Technology Packaging
and Dissemination. Fibre Crops Agricultural Product Value Chains (APVC)
Analysis Workshop, 26th - 28th April 2011, Egerton University Njoro, Kenya.
o Gitonga, W, Macharia, JM K, Mungai, A, Njue, H, KARANJA, DK and Olweny,
H (2010). Cotton Production Constraints and Research Interventions in Kenya.
10th Meeting of the Southern and Eastern African Cotton Forum (SEACF), 9th –
10th March 2010, Lusaka, Zambia
 Journal Article
o D Karanja, R Musebe, W Gitonga, L Cossa, A Mungai, J Macharia, A Gitunu, A
Gikandi, L Muthoni, J Flood and M Kimani. Comparative analysis of production
practices and post-harvest handling of cotton by smallholder farmers in Kenya and
Mozambique. Cotton Research Journal, July – December 2012. pp. 202 -212.
 Video links
o www.youtube.com/watch?v=5K3nQ43aq8k
o www.firstpost.com/.../mozambique-cabi-cotton-julie-flood-video- 5K3nQ43aq8k7086-1.html
39
IV. Lessons Learned
4.1 Development Lessons
There were limitations in undertaking specific studies for tracking the purpose level
indicators due to financial constraints, which ought to be taken in to account during the
project design.
In Mozambique, the strip intercropping of cotton and food crops (maize and soybeans) being
promoted was thought to contribute towards increased participation of women in the FFSs,
given that women spend time in the production of food crops. However, as rural women are
fully occupied during the growing season with doing that- growing food and doing household
chores, there was relatively low participation of women in the FFSs. In the establishment of
future FFS, social factors such as this need to be taken into account so as to increase women’s
participation.
It was observed that introduction of the ICM practices led to improvements in the welfare of
the cotton growers in both Kenya and Mozambique. Inspection of the level of improvement
revealed a better case scenario for the farming community in Kenya. This may be attributed
to good response rate to inputs in Kenya compared to Mozambique and the associated
production for the different areas under cotton. The Cotton farmers in both Kenya and
Mozambique demonstrated better cohesion and access to information. Marketing skills for
the farmers in Kenya were at relatively better level compared to those in Mozambique
possibly due to the need to identify prospective buyers rather than depending on designated/
preselected buyers by the government. The cotton growers in Mozambique were supplied
with inputs by the cotton companies and on average reported some better degree of
satisfaction in terms of consistency compared to the Kenyan counterparts who purchased
inputs on their own. A combination of ICM practices and good marketing of inputs and
outputs is therefore likely to guarantee sustainable incomes for the cotton growers in both
Kenya and Mozambique.
Improvements in cotton productivity and returns would require systems that allow learning
by doing. The ability of the cotton sector to ensure a high participation of private and public
sector personnel in training is vital for successful implementation of producer targeted
programs. For successful implementation of an input supply scheme, there is a need to build
trust between farmers and extension agents and the management of cotton companies/ginners,
and to improve company logistics.
4.2 Operational Lessons
The baseline survey conducted by the project revealed that the majority of farmers had low
education levels and in some cases could not read. As a result, the FFS sessions were
conducted in local languages. A manual on integrated crop and pest management in cotton,
and posters and leaflets on integrated pest management were distributed to trainer and
farmers, containing clear illustrations, pictures and diagrams to facilitate the identification of
pests without having to read. In future, provision of audio visual material such as training
videos in the local languages could facilitate the learning process.
40
The members of the farmer field schools (FFS) noted that the activities enabled them to
interact better with their colleagues and exchange ideas and hence improve on planning and
sharing of roles. There was also good interaction between the farmers and the staff of the
cotton companies/ginneries and the farmers’ access to information.
Most of the FFS were strategically established in areas located near the plots of members.
This facilitated the interaction and increased participation of farmers in the FFS activities,
and also enabled them to take advantage of economies of scale in access to information and
exposing them to a variety of new ideas, new knowledge, new techniques, new situations, and
new ways of responding to problems.
The one hectare FFS plots in Mozambique encouraged many smallholders to start cultivating
larger areas of cotton on their own. However, some FFS members dropped out due to the
relatively high workload in the 1 ha FFS-plots in addition to their own cotton and food crop
fields. A few farmers quit because they expected to be paid for weeding and harvesting, or to
get free inputs (spraying pump, protection gear and certified seeds). This emphasizes the need
to ensure that farmers understand the main objective of the establishment of FFS, which is
farmer empowerment through capacity building and training on good production practices.
At the beginning of the project, participating farmers got the opportunity to use adequate
production inputs such as certified seeds, pesticides, fertilizers and herbicides in the FFSs
plots. However, these inputs were not available locally for them to use in their own fields. To
address the lack of input supply, alternative input supply mechanism through a network of
local input suppliers in all cotton production areas including the project target districts were
identified. Through stakeholder dialogue, the programme sought to increase accessibility of
inputs.
Farmer Field Schools, ICM and all other productivity enhancing approaches require
extension staff with passion for the job, good technical background and facilitation skills.
Through the ToT workshops conducted by the project in Kenya and Mozambique, a large
percentage of the extension workers were trained and were available and adequate for
mentoring as trainers. The trained extension workers did not require more than the usual
input of expert trainers to make them effective trainers of others. However, the poor retention
of extension workers by the cotton companies in Mozambique in some cases affected the
development and continuation of FFSs. As these experienced extension officers who were
already familiar with the ICM approach were constantly leaving the companies, the newly
hired ones had to go through new training to facilitate the FFSs, and this slowed down the
qualitative development of the FFSs. Hence, development of a sustainable system very much
depends on retraining experienced extension workers as learning facilitators. Further studies
of why the extensionists left could be undertaken in future
During the project formulation stage, there was an assumption that FFS-groups established in
the first year would not need a facilitator in subsequent years. However, this was an
optimistic scenario given that farmers would not fully adopt the entire ICM-technology
package in the first year. Hence the project identified the need to facilitate the second year
FFS-groups with a reduced number of visits by the FFS facilitator.
Given the substantial amount of monthly work time (at least 50%) required for FFS, an
approach allowing selected staff of the lead organisations and cotton companies committed to
41
FFS, ICM development would be necessary so as to gather the critical, sustained capacity in
the country.
The participation of stakeholders such agrochemicals in such training and school teachers
used as interpreters makes a very fertile ground for sustaining the development of FFS and
ICM.
The main implementation challenges for sustainability of FFS are linked to: i) effectively
integrating FFS and ICM in the mainstream extension activities of the cotton companies or
ginneries; ii) supporting cotton companies or ginneries to view ICM concepts as a key
approach to productivity enhancement, and so providing adequate staff time in comparison
with that for other core business areas of merchandizing and ginning; iii) fitting the relatively
lengthy training sessions in the regular work of companies especially during the cotton
growing season and iv) getting the private sector players to supplement financial resources of
the project for sustainability.
The temporary suspension of the project by CFC in 2012 impacted negatively on the project
activities. This delayed execution of the situation analysis for the new districts (Lalaua and
Ribaue), so the baseline data was only finalized in December 2013. The suspension occurred
in mid-season thus impacting negatively on monitoring/ mentoring at on-going FFS and no
new FFS were established in Kenya. After the lifting of the suspension, the project budget
cuts resulted in changes in project work plans. Given that implementation of the ICM
technologies through FFS is season based, this led to cancellation of certain activities such as
organising field days and graduation for FFS members as well as the establishment of new
FFS during the 2012/13 cotton cropping season in Mozambique. Similarly, the reallocated
funds were not sufficient to establish new FFS in Kenya. Further the PIA indicated that the
funds were inadequate to do any systematic impact assessment, which is why the results
reported above are for Mozambique only.
42
V. Conclusions and Recommendations
5.1 Conclusions
The ICM practices were used to different extents by the cotton growers in the different
districts. Integrated pest management including rational use of pesticides and proper spacing
of cotton were the ICM practices most preferred by the farming community. Intercropping,
although noted to be a key ICM practice was less used by the farming community in
Mozambique. Given the need for provision of options for purposes of improving cotton
productivity it is necessary for the cotton farmers to be advised on the importance of
intercropping. The rational use of pesticides by the ICM farmers in the project areas as
demonstrated by less expenditure on pesticides suggests the need for up-scaling the training
to other cotton growers.
The cotton yields received by the ICM cotton growers were relatively higher than those of the
non-ICM cotton growers and those of the control districts although this was not significant
the trend was seen and perhaps if training had continued then significant effects would have
been seen. This demonstrates the importance of the ICM practices. There is a need therefore
to extend the ICM practices to the other cotton farmers in the respective countries. Scaling-up
of the practices needs to be accompanied with the formation of active and effective groups
that are legally constituted to be able to source for other services. This is attributed to the fact
that the farmer field school members indicated they were better able to interact with the
cotton companies as a group. Interactions among the cotton growers established ownership of
services and better planning.
The ICM practices contributed to the cotton growers’ incomes through better yields and
reduction in pesticide costs. Farmers can make better use of the benefits obtained from the
use of ICM by undertaking cotton production as a business activity. In this regard, activities
that enhance business processes need to be integrated. Among these are appropriate record
keeping and budgeting. The members of the farmer field schools noted that they were able to
plan and work effectively as a team. This suggests that training in group dynamics may be a
key to assuring the pooling of resources by the farmers and hence encourage group
production as well as information sharing among the group members. The groups formed
need to be encouraged to operate in a manner that is consistent with the operations of
innovation platforms in order to be able to interact effectively with other stakeholders.
The cotton enterprise is a key contributor to the incomes of the farming community in the
project areas. However, a relatively lower proportion of land is devoted to cotton production.
During the project period there was some increase in the land devoted to cotton production,
and this indicates that there is potential for increasing the area under cotton production in
appropriate agro-ecological zones. However, it is necessary to provide more technical knowhow to the cotton growers coupled with promotion of cotton as a profitable enterprise.
5.2 Recommendations
On basis of the above, it is recommended that the national cotton bodies need to:
 Follow-up on the training of trainers and farmer field schools initiated by the project. This
should include a further critical assessment of the trained FFS facilitators and possible
43


identification of other staff from across stakeholder institutions that can be further trained
and committed to country wide promotion of the FFS and ICM approaches.
Assesses the feasibility of entering into partnerships with private sector institutions and
NGOs for purposes of supplementing project resources to enhance the adoption of FFS
and ICM approaches. Companies could, for example, pledge to provide cheap monitoring
tools and training materials, and provide free/subsidised venues for training etc.
Make a thorough evaluation of the four potential implementation challenges identified in
Section 4.2
44
Annex 1: Project Logframe
Narrative summary
Objectively verifiable
indicators
Means of verification
Assumptions
Goal:
Reduce rural poverty, improve farmers’ livelihood, and promote
By end of project, improved ICM
sustainable agriculture in cotton based cropping systems in Kenya and strategy promoted in order to
Mozambique
achieve beneficial impact on
livelihoods of poor people and, are
contributing one or more of the
following:
• Increased and/or stabilised
production
Reports of target organisations Conducive agricultural policies of
governments and commitment of
Programme and external
participating organisations
evaluations
Political stability in Kenya and
Reports of national and local
Mozambique
level surveys of improved
benefits (productive capacity,
food security, wealth, nutrition
and environment).
• Increased productivity (yields/ha,
Impact assessment reports and
land use, labour, capital)
government statistics of
• Reduced use of banned &/or
agricultural productivity
restricted pesticides
• Enhanced marketing
opportunities
Purpose:
To improve cotton production efficiency through formulation and
promotion of innovative ICM options in the cotton production systems
in Kenya and Mozambique by involving private enterprises and public
organizations
a. Cotton yield in participatory
Trade statistics by cotton
Cotton yields are not affected by
trial demonstration plots is at least associations.
adverse climatic conditions or
50% of a best variety field trialled
unprecedented pest attack
Statistics by the national cotton
in country
bodies.
b. Pesticide use reduced by 50%
End-of-project impact
by farmers participating in the
assessment report
project
c. Net income of farmers
participating in the project
increase by at least 30%
Outputs:
45
1. Best practice ICM packages formulated
2 Training of Trainers Workshops Reports, training manuals
held
25-30 resource persons trained per
TOT
Circumstances at the time of the
formulation of the ICM strategy do
not change significantly prior to
implementation of the training
Willingness of ginneries to commit
resources to produce training
manuals
2. Promotion and adoption of ICM packages
240 Farmer Field Schools
established
Numbers of farmers attending
FFS
Number of farmers adopting the
formulated ICM package
Reports from FFS
Net income to farmers improved
Surveys reports confirming
adoption
4 Stakeholder Awareness
Workshops planned and held
Stakeholder linkages established
Availability and willingness of
potential trainers/farmers
Farmers have ready access to
required Inputs
50% reduction in pesticides use
3. Stakeholders linkages built for sustaining ICM
No unusual adverse biological or
biophysical effects on cotton
production
Project progress report,
Local actors in cotton value chain
including semi-annual reports, maintain positive relations
workshop reports
Lessons learned and best practices
widely circulated
4. Impact study of ICM adoption made
Data on benefits of ICM, available Impact assessment reports
by end of project
Project reports, Publications.
Impact is seen within the timeframe
of the project
5. Project management and coordination
Project outputs delivered as per
the logframe
Reports of PEA and PIAs and
collaborating institutions
Resources are available and in good
time
Project documentation –
reports, training materials
curricula produced
Stakeholders and partners are willing
and able to participate in needs
analysis
Activities:
1. Best practice ICM packages introduced
1.1 Participatory analysis of needs and constraints of farmers and
markets undertaken
1.2 Analysis of farmers’ existing agricultural practices, production
patterns, post-harvest handling conducted
46
1.3 Appropriate ICM models and Training of Trainers curricula
formulated
Ginneries are willing to support the
project
1.4 Ginneries supported in the production of quality training and
promotional materials on best ICM strategy
2. Promotion and adoption of ICM packages
2.1 Identify individuals that will act as trainers (facilitators) for the
FFS demonstrations plots
Project documentationStakeholders and partners are willing
workshop reports, training
and able to participate in training
materials and curricula for FFS
and TOTs;
Suitable candidates as trainers are
Dissemination outputs
available
2.2 Conduct training of trainers (ToT) workshops
2.3 Selection of demonstration sites from existing FFS
2.4 Establishment of on-farm demonstrations plots within selected
FFS
2.5 Conduct farmer-participatory agro-ecosystem analysis (AESA) at
selected demonstration sites
2.6 Mentor and backstop trainers as they train farmers
2.7 Dissemination of best ICM strategy through farmer field days and
mass media
3. Build stakeholder linkages for sustaining ICM
3.1 Conduct stakeholder mapping of value chain and produce plan for
workshop
Project documentation, value
chains mapped; workshop
plans and reports
3.2 From 3.1 conduct a workshop annually to plan /review pilot
schemes in each country
Stakeholders and partners are willing
and able to interact
Pilot schemes planned and
implemented; results
synthesized and lesson learned
disseminated
3.3 Implement pilot schemes
3.4 Final stakeholder learning workshop- sharing lessons learned on
pilot schemes
4. Impact assessment of ICM adoption made
4.1 Conduct Baseline Survey (linked to activity 1.3) to establish preadoption socio-economic situation and production practices
Survey reports available
4.2 Conduct impact assessment (before and after analysis)
Impact reports available
4.3 Synthesise and analyse the findings( compare adopting vs no
47
No factor external to the project has
had a negative effect on the impact
of the project such as cotton farmers
decide to grow other crops between
adopting farmers)
start and end of the project
4.4 Disseminate the findings of the impact assessment
Findings disseminated
5. Project management and coordination
Procedure manual
5.1 Support organization of an inception workshop and support
establishment of CFC administrative and accounting procedures and
train local counterparts in project procedures
Report of inception workshop
Quarterly financial reports
Financing from all sources made on a
timely basis in tandem with proposed
activities & annual work plan, budget
etc.
5.2 Advise on operational procedures and initiate consultancies where
necessary
Progress reports, mid-term
evaluation report, annual
accounts and audits, project
completion report
Personnel, including external
consultants, competent in required
skills can be identified & commit to
project activities
Work plans produced
The PEA & partner institutions coordinate & execute project
efficiently.
5.3 Assist PIAs and ICAC to prepare necessary documentation,
including budgets and work plans.
5.4 Liaise between project donors and implementers and arrange
exchange visits
Visit reports produced
5.5 Monitor project progress and report on inputs (disbursements),
activities undertaken and outputs achieved (to include mid-term
impact review and expenditure audits).
All project participants remain
committed to project purpose.
Socio-political developments do not
prevent effective project
implementation
5.6 Assist PIAs and partners with planning and co-ordination of
activities aimed at providing uptake pathways for outputs
5.7 Prepare regular progress reports, mid-term evaluation report,
annual accounts, audits and project completion report.
48
Annex 2. Curriculum for training of trainers
Cotton ICM
Module
Principles of
Cotton ICM
Farmer Field
Schools
Objectives
TOT Participants will:
Understand and apply the
concepts of ICM.
Give pros and cons of pesticide
usage.
Understand the farmers field
school methodology and
become good FFS facilitators
Topics
Facilitation Methods/Activities
 Growing a healthy crop
 Conservation of natural enemies
 Cotton ecology and ecosystem
analysis
 Yield optimisation
 Reducing pesticide usage with IPM
 Results of the baseline study
(socio-economic, biological training
need assessment)
 Overview of farmer field school –
historical background
 Introduction to FFS methodology
(what is FFS)
 Characteristics of FFS
 Objectives of FFS
 Principles of FFS
 Steps in conducting FFS
 FFS study site selection and farmers
recruitment
 Typical FFS day
 Agro ecosystem analysis (field
observations)
 AESA format and typical FFS
timetable
 Participatory technology
development (PTD)
 Case studies
 Group discussions
 Field exercises
 Presentation
49
 Presentations
 Group discussions
 Exercises
 Role play
 Hands on discovery learning exercises
 Group dynamics
 Energizers
 Simulations
 Planning exercises
 Field observations
Cotton ICM
Module
Objectives
Topics
Facilitation Methods/Activities
TOT Participants will:




Cotton Pests and
their
Management
Cotton
Agronomy
Marketing
 Identify pests affecting
cotton and understand
various control methods
(chemical, physical, cultural
and biological)
 Appreciate the ways in
which indigenous
knowledge can contribute to
ICM.
 Be able advise farmers on
best agronomic practices in
cotton farming
 Understand the various
marketing and processing
methods for cotton.
 Understand policies
affecting cotton industry.
 Be able to advise farmers on
Facilitation skills
Communication skills
Field day and graduation ceremony
FFS curricula and work plan
 Insect pests of cotton (identification,
damage symptoms, IPM)
 Diseases of cotton (identification,
symptoms, IPM)





Presentations
Field visits
Group discussions
Field exercises
Specimen of pests and diseases




















Presentations
Field visits
Group discussions
Field exercises
Specimen of seed cotton
Posters of developmental stages
Seeds
Fertilisation
Weeding
Planting
Land preparation
Intercropping
Thinning and gapping
Growth and development stages
Ginning
Weaving
Spinning
Cost-Benefit analysis
Record keeping
Budgeting
50
 Visit micro-gin at KARI Mwea
 Presentations
 Field exercises
 Samples of cotton products and
packaging materials
Cotton ICM
Module
Objectives
TOT Participants will:
value addition.
Harvesting and
Post-Harvesting
Cotton Business
Management
 Be able to advise farmers
how to harvest and store
cotton without
compromising quality.
 Be able to identify and
describe the different grades
of cotton.
 Be able to advise farmers on
ideal transport and weighing
methods.
 Advise farmers on various
sources for obtaining inputs
and credit.
 Advise farmers on
negotiation of binding
contractual agreements with
other stakeholders.
Topics
Facilitation Methods/Activities










Cotton Value Chain
Liberalisation
Pricing
Quality control
Value addition
Grading
Storage
Packaging
Transport
Weighing




Input supply
Credit information
Contractual arrangements
Financing
51
 Visit micro-gin at KARI Mwea
 Presentation
 Field exercises
 Presentations
 Exercises
 Group discussions
Annex 3. Steps in conducting Cotton ICM FFS - The model
1. Conduct ground working activities (this was done through baseline studies and
community mobilisation campaigns)
 Identify priority problems in cotton production and protection
 Identify solutions to identified problems
 Establish farmers’ practices
 Identify participants for field school
 Identify sites for field school
2. Develop ToT curriculum for FFSs (this was done through workshops held at KARI
and IAM)
 National steering committee organise a workshop
 Cotton experts (agronomists, entomologists, soil scientists, participatory training
experts, social economists, private sector, innovative farmers) invited as resource
persons
 Curriculum developed based on results of the ground working activities
3. Training of Facilitators on: (ToT courses were done in Embu, Lamu, Beira and
Nampula)
 Cotton ICM
 Field guides on how to effectively deliver cotton ICM topics using non-formal
education methods (NFE)
 Participatory technology development (PTD) with emphasis on the approaches and
developing guidelines on conducting PTD
 Non-formal education methods with emphasis on what, when and how to use NFE in
FFS
 Group dynamics
 Special topics to be addressed at every stage of training.
4. Establishment and Running FFS
With the guidance of facilitators, the group meets regularly throughout the season, and
 Lays out and designs the FFS study plot (0.2-1 ha)
 Implement PTDs (Test and Validate) on cotton ICM technologies (soil sampling and
analysis, nutrient management e.g. application of lime, manures and inorganic
fertilizers, pest and disease control, land preparation and dry planting, strip
intercropping, rotations, weed management, harvesting and sorting)
 Conduct agro-ecosystem analysis ( AESA) - collect, process and present the data
 Discussions and decision making
 Group dynamics
 Special topics
 Implement AESA recommendation on the FFS study plot
5. Evaluating PTDs
 Analyse collected data
 Interpret
 Economic analysis
 Presentation
52
6. Field days
 During the period of running the FFS, field days are organized where the rest of the
farming community is invited to share what the group has learned in the FFS
 One or two field days per season
 Farmers themselves facilitate during this day
7. Graduations
 This activity marks the end of the season long FFS. The farmers, facilitators and the
coordinating office usually organize it.
 Farmers are awarded certificates
8. Follow up by facilitators
 Occasionally the core facilitators will follow-up on schools that have graduated
preferably on monthly basis.
53
Annex 4. Checklist of what one can expect from a quality Farmer Field School (FFS)
Group profile
 Group registered with relevant authority
 Ideal membership: 20-30
 Common interest and fairly homogeneous group
 Group by-laws & constitution
 Gender, age and literacy mix
 Sustained attendance rates
FFS facilitator
 Trained in FFS methodology by qualified FFS trainer
 Trained in leadership skills
 Facilitating not lecturing sessions
 Facilitator must be available and accessible for the farmers
 Horizontal interaction
 Creative and innovative
 Facilitator technically capable
 Resourceful and with good attitude towards farmers opinion
 Accountable to farmers
Group management and discipline
 Good time keeping
 Attendance (70-80%) minimum by all members
 Good attendance during each session
 Learning and group norms-available and strictly followed
 Gender equality within the group
 Transparency in financial management and decision making
 Time table of sessions being followed
 All members understand group rules
 Equal rights and mutual respect
 Roles of members, officials and facilitators well understood
 Good leadership and structure
 Democratic practices during elections of officials
 Timeliness of special topics
Learning process
 Curriculum agreed on by farmers
 Curriculum should allow for cross cutting issues and special topics
 Curriculum fitted to real life situation
 Curriculum should be all inclusive and flexible
 Environmental concerns should be addressed
 Marketing training included
 Well balanced group activities
54
Group experimentation
 Should have a learning site including field trials
 Demand driven enterprise choice
 Agro-Eco System Analysis (AESA) carried out regularly
 Comparative studies (not demonstrations)
Documentation
 Good documentation of planned activities
 Membership records
 Enterprise records-well kept
 Attendance-records/register well kept
 Monitoring and Evaluation-documented
 Good documentation and record keeping
 Minutes/records of each session well kept
 Using documented observations and results for decision making
Plans




Clear objectives and goals of the group
Stated / known “mission” and “vision” of the FFS
Availability of activity plan and implementation
Well planned daily time table
Sustainability
 Ability to mobilize local resources
 Group cost sharing
 Linkages with other approaches / projects
 Availability of Income Generating Activities (IGA’S)
 Have in-build Participatory Monitoring and Evaluation (PM&E) system.
 Developed exit plan
Signs of empowerment
 Farmer confidence
 Farmer ownership of process
 Able to seek and share information (within and outside group)
 Farmer understanding FFS concepts and technical issues
 Active, motivated and confident members
 Farmer participation in decision making processes
 Active participation by all FFS members
 Sense of innovativeness
 Well informed decision making capacity
Outcome trends
 General improvement in members households
 Financial empowerment
 Adoption and adaptation of improved practices by members
55
Annex 5. Components of cotton ICM in Farmer Field Schools in Mozambique
Pest management
Preparation of land:

Manual and mechanical (tractors provided by SANAM) – September throughout
October 2010 season 2010/11.
Planting:
Planting was done from 15th of November 2010 to 15th of January 2011. Farmers have to
plant cotton as soon as the first rains start.


Due to late rains most ICM FFS sowed seeds in December 2010 and January 2011.
Sowing was done in a uniform area where cotton had not been cultivated in the past
three consecutive crop seasons.
 Rotation: cotton-leguminous-cereals-cotton.
 0.5 ha local practice - planted “local” cotton seed variety CA-324 provided by
SANAM as a common practice within a concession. Mono crop.
 0.5 ha ICM study plot – planted improved cotton seed variety CA-324 (certified) from
CIMSAN acquired by the Project. All improved cotton seeds were chemically treated
with Fungicides (Imidacloprid or Thiametoxam)
 Strip intercropped with improved seeds of maize variety Matuba (local breeder) and
one FFS in Mecuburi with soya beans. Improved maize variety acquired by the
project at local provider (widely available) and soya beans provided by
TECHNOSERVE/USDA Project.
 Spacing: 100 cm within the row by 20 cm within plants in a row. For both local
practice and ICM plot.
 Seeds per hole: 4-5 with germination rate of 80% and above. Applied mostly for the
ICM plot since germination rate of certified seeds was higher.
 Strip intercropping: proportion 3:1. Twelve row of cotton followed by four rows of
other crop (maize, pigeon pea, soya beans and sorghum). Applied in all ICM plots
including the one with soya beans.
Thinning:
 9-12 days after germination (1-2 vigorous plants per hole). Applied in both plots.
Weed Management:

ICM FFS practice to maintain a totally weed-free crop and treat weeds in a timely
manner.
 In average done in 3 stages manually. 1st weeding occurs simultaneously with
thinning. Labour for weeding is scarce. That will be addressed in the season 2011/12
with application of herbicides.
Main pests:
 Aphids, Jassids, Bollworms (American, red and spiny) and cotton strainers.
Pesticide application scheme:



3 week after germination 1st treatment - Acetamiprid (volamiprid 22.2% SL) against
sucking insects. Foliar.
5-7 weeks after germination 2nd Treatment Lambda – Cyhalothrin 60g/l +
Acetamiprid 40g/l (Zakanaka Top 10% EC) against sucking insects and bollworms.
Foliar.
7 - 9 weeks after germination 3rd treatment Lambda – cyhalothrin 60g/l (Zakanaka k
6% EC) against bollworms.
56
9 – 11 weeks after germination 4th treatment Lamba – cyhalothrin 48g/l + Profenofos
(Zakanaka Pro 64.8% EC) against bollworms.
 11 – 13 weeks after germination 5th treatment Lamba cyhalothrin
 13 – 15 weeks after germination Lambda – cyhalothrin + acetamiprid (Zakanaka
top10%) against bollworms and sucking insects
 Local practice application was carried out purely based on calendar.
 For the ICM plot AESA and IPM practices including observations, scouting, cultural
and mechanical methods were applied. After that chemical treatment with the same
product followed.
 Chemical rotation will be tested for next season. Hence, in 2011/12 season a different
combination of insecticides with less hazardous chemicals and more biological
products will be used.
Spray technology:


Micron ULVA+ (ultra-low volume) that uses both 1 and 5 litres containers with 5
batteries for insecticides and 3 for herbicides (season 2011/12). Ultra low volume
sprayer commonly used in Mozambique among small-holders in Cotton. Chemicals
were carefully applied using protective gear. The entire set of equipment acquired by
the Project. For cultural reasons female farmers do not usually apply chemicals in the
cotton field.
Harvesting and Post-Harvest Handling:

Manual harvesting was done in two stages. Sorting during harvest in the field and on
drier usually at farmers’ house. Two grades of seed cotton, 1st and 2nd grade
respectively. Bags (jute) provided by SANAM. Driers prepared using local materials.
Note



Chemical (Zakanaka)
Cultural (treated seed)
Mechanical (crashing after early detection when numbers are low)
57
Annex 6. Market Assistance Programme: Cotton Intervention Logic (Makueni & Nyanza Ginneries) – Source CODA
_ _ __ _____ ____ ____ __ ____ _ _ _ _ _ _ _ __ _ __ _ _ _ _ _ __ _ _ _-__ _ _ _ _ _ _ _ _ _ _ __ _ _ __ __ __ _ _ _ _ _ _ __
Poverty reduced by over 30%
POVERTY
REDUCED
Farmer incomes increase by over 50%
ENTERP
RISE
_LEVEL
__ _____
CHANGE
_
_____
Service providers do business profitably and sustainably with cotton farmers, farmers’ income from cotton increases
____
____100%
__ ____ _ _ _ _ _ _ _ __ _ __ _ _ _ _ _ __ _ _ ___ _ _ _ _ _ _ _ _ _ _ __ _ _ __ __ __ _ _ _ _ _ _ ___ _ _ _ _ _ _ _ _ _ _ _ _
by over
Farmer yields double hence improving productivity
MARKET
SYSTEM
CHANGE
Cotton farmers access and use
extension service (credit, inputs,
weather index insurance, cotton
crop husbandry information etc)
__ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
______
ACTIVITIES
Stable seed cotton prices
encourage more farmers to
grow cotton and existing
ones to increase acreage
Price of Cotton seed is
fairy determined with
_ _input
_ _of all
_ actors
_ _ _ _
1. Assist ginners in designing the roll-out and
identifying CF areas
2. Assist ginners set up input supply (seed, pesticide
& fertilizer) mechanisms
3. Assist ginners set up ploughing/ripping services &
equipment hire mechanisms
4. Facilitate the development of demonstration sites
5. Building capacity of ginners to manage farmer-out
grower groups to manage the implementation of CF
6. Building capacity of ginners to provide extension
service using agents from the community who train
farmers, distribute inputs, buy seed cotton & do PR.
The agents are paid a retainer and commission on
input sales and cotton collections
INTERVENTION 1: Contract farming
Models
_
Farmers use certified (delinted and
treated) cotton seed. Farmers are able
to appreciate benefits of using
certified seeds
Cotton seed production and
certification system put in place and
_ Kenya
_ _ _Seed
_ _Company
_ _ _(KSC)
_ _ produce
____
certified cotton seed. Farmers access
good planting material
1. Link ginners and their farmers to financial
institutions and insurance companies
2. Facilitate the financial institutions and
insurance companies to design suitable
products for ginners and farmers
3. Investigate the potential of establishing a
sector wide stabilization fund
INTERVENTION 2: Sustainable
financing & risk management mechanisms
58
Farmers’ access
agronomic and market
information via SMS
_
Cotton market and
Agronomy database is set
_up_and_farmers
_ _ _can_ _ _ _
access it via SMS
1. MAP facilitates the seed
taskforce set up by CODA
and KSC to come up with a
seed business plan
2. MAP builds the capacity
of KSC to commercialize
cotton seed
INTERVENTION 3:
Certified seed
_
Credit finance (CF) models that
prove acceptable to majority of
actors is adopted as the way of
doing cotton production in Kenya
and included in the Cotton Policy.
_Data
_ _collection
_ _ _ is_streamlined
_ _ _ _ and
__
actors are able to use it to make
informed decisions
1. Facilitating design of
SMS based system to
disseminate cotton
production and market
information
INTERVENTIO
N 4: ICT platform
to disseminate
cotton information
___
1. Engaging sector actors to define
common vision for cotton sector
through w/shops for sector policy
revision
2. Coda is designing and
implementing data collection
system
3. CODA is enforcing CF contract
agreements
INTERVENTION 5:
Enhancing capacity (CODA)
Annex 7: Baseline survey report for Kenya
ICAC
IMPROVING COTTON PRODUCTION EFFICIENCY IN SMALLSCALE FARMING SYSTEMS OF KENYA THROUGH BETTER
VERTICAL INTEGRATION OF THE SUPPLY CHAIN (CFC/ICAC/37)
COTTON BASELINE SURVEY REPORT FOR KENYA
59
Executive Summary
A cotton baseline survey was conducted in six project districts and three non-project districts
in Kenya that covered the main cotton growing areas. The project districts covered were
Lamu West, Kitui West, Kathonzweni, Baringo North, Tana River and Tharaka South. The
non-project districts were Makindu, Magarini and Baringo Central. The purpose of the
baseline survey was to identify the cotton production patterns, processing and marketing as
well as the needs of the cotton growers. The survey also set the benchmarks for assessing the
impact of the project activities. The approach used was the household survey encompassing
key household socioeconomic characteristics, focus group discussions and key informant
interviews. Fifty farmers were interviewed in each district and one focus group was
conducted in each of the districts. The focus group members comprised the key cotton
stakeholders in each district and membership ranged from 9 to 15. Purposive sampling was
adopted for the household survey whereby the major cotton producing division in each
district was chosen and the respondents were farmers who used to grow cotton before or
those who had a cotton crop in the field during the time of the survey.
The average age of the household heads were 50 and 53 years for beneficiary and nonbeneficiary samples respectively. Majority of the household heads were male and the mean
household size was 7 for the beneficiary districts and 8 for the non-beneficiary districts. Most
of the household heads had attained primary level education and their main occupation was
farming. Forty five percent of the households in beneficiary and 54% in non-beneficiary
districts owned semi-permanent houses, 38% and 40% had traditional and the remainder
owned permanent houses. Mean land sizes for the sampled households were 4.1 and 4.6
hectares for beneficiary and non-beneficiary districts respectively. Forty nine percent of the
households in beneficiary and more than half in non-beneficiary districts owned land without
title deeds.
The mean cotton acreage was 0.76 and 0.57 hectares in beneficiary and non-beneficiary
districts respectively. Farmers ranked cotton as the most important among the crop
enterprises in the beneficiary while it was ranked second to maize in the non-beneficiary
districts. There was minimal mechanization in carrying out various activities in cotton
production. Pesticide application was the major method of pests/disease control. There was
minimal application of organic and inorganic fertilizer and cotton farmers hardly use
herbicides. Less than ¼ of the households in both areas ratooned cotton while more than ½
practiced crop rotation on ad hock basis. Less than half of the interviewed households in both
areas indicated that they had engaged in contract cotton farming. Sorting of cotton into
grades A and B at farm level was mainly done after harvesting of the seed cotton. More than
half of the farmers interviewed had a cotton crop in the field during the survey period with
most intercropping. The key constraints to cotton production were low prices, pests and high
cost of pesticides, insufficient capital and delayed payments. Cotton production was
undertaken using financial resources obtained from the sale of livestock and other farm
produce as well as borrowing from fellow farmers. There is potential for using farmer groups
to improve cotton productivity. Farmers suggestions on how to improve cotton productivity
included, improvement of seed cotton prices, training on good agronomic practices including
post-harvest handling, use of high yielding varieties, provision of loans or credit and input
subsidies. The survey results suggested a need for short duration cotton varieties, training of
the cotton growers on good production practices and cotton grower participation in cotton
marketing. There was also a need to introduce a credit scheme to facilitate cotton production
processes.
60
1.0 Introduction
1.1 The Cotton Sector in Kenya
Agricultural growth and development is crucial to Kenya’s overall economic growth. The
sector contributes about 26% of Gross Domestic Product (GDP) and a further 27% through
linkages with manufacturing, distribution and the service sectors. About 80% of the
population live in the rural areas and depend mainly on agriculture and fisheries for
livelihood. In addition, the rural farming community constitutes 87% of all poor households
(KAPP, 2007).
Kenya’s economy has performed below its potential in recent years. In the past two decades,
agricultural productivity has declined and competitiveness eroded. Poverty and food
insecurity have increased. About 50% of Kenyans are food insecure and significant potential
for increased production remains largely unexploited. Kenya’s agricultural sector mirrored
the poor performance of the economy more generally during the same period. Average annual
agricultural GDP growth fell from 3.5 percent in the 1980s to 1.0 percent during the 1990s
(KAPP, 2007).
The cotton subsector in Kenya was once the most thriving sector in the agricultural economy
because of its contribution not only in the rural economy but also in the manufacturing sector.
The cotton industry has a huge potential to offer employment since it is labour intensive and
has opportunities to generate small scale and micro-enterprise activities in the national
economy. Income derived from cotton production and employment is very vital for food
security, poverty reduction and wealth creation especially in the marginal areas which
occupies about 87% of Kenya’s land mass (Ikiara and Ndirangu, 2002).
The subsector was doing well during the 1970’s and 80’s until its liberalization in the 1990’s.
It was also adversely affected by the export ban slapped on Kenyan textile products in the
USA market in 1994. These factors saw lint production drop to an annual average of 20,000
bales, despite the country’s large potential estimated at 300,000 bales (Ikiara and Ndirangu,
2002) under rain fed conditions. In addition to low cotton production, many ginneries and
textile and apparel manufacturers collapsed following liberalization, leading to enormous job
losses. The textile and apparel industry, consequently, lost its key positioning in the
manufacturing sector and the economy. The introduction of the African Growth and
Opportunity Act (AGOA) in 2000 by the U.S.A created a new momentum in the industry,
especially at the garment making part of the value chain.
Currently a production level of 30,000 bales has been achieved (CODA, 2009). The annual
demand from the domestic textile industry is 120,000-140,000 bales. The shortfall is met
from the import market in the form of lint, seed cotton, yarn, fabric, old and new clothes.
The Poverty Reduction Strategy paper 2000-2003 identifies the cotton industry as one of the
sub-sectors targeted for fighting poverty especially in the marginal rainfall areas (GoK,
2003). The vision 2030 further emphasizes the importance of the cotton industry to enhance
economic growth of the country’s marginal areas. It is estimated that about ¼ of the country’s
population can benefit from the cotton industry. It is in this regard that the government with
the support of other external agencies is supporting the revival and development of the
industry.
61
Small scale seed cotton production in Kenya is characterized by low production per unit area.
The area under cotton production is estimated at 40,000 ha against a potential of 385,000 ha
(CODA, 2009) while vulnerability to low cotton prices has often resulted to farmers growing
alternative crops. Production can however be improved by placing the initial emphasis on
profitability for the grower, rather than increased yields. This can be addressed by ensuring
that systems are in place to maximize the benefits of input use through promoting integrated
crop management (ICM), backed by greater investment in the provision of technology and
associated support services. Improved access to technology and the support to improve
farmers’ knowledge of cotton ICM will improve the efficiency of input use that in turn, will
encourage more farmers to grow cotton and lead to increases in national production as well as
increasing the average yield. This is the gap that the CFC/ICAC/37 Project intends to fill. The
project specifically addresses the stated gap between production efficiency at research farms
and the significantly lower yields obtained in small-holder production situations.
This report contains analysis of a baseline survey conducted to understand the current
situation of cotton production in Kenya through participatory analysis of needs and
constraints of farmers and markets. In addition, the baseline data was instrumental in
assessing final impact of the project by comparing the project with the non-beneficiary
districts.
1.2 Objectives of the survey
1. Assess existing agricultural practices, production patterns, post-harvest handling
The intention was to assess the methods used in production, area under cotton in the
various districts, cotton varieties, characteristics of the cotton growers, access to the
factors of production, processing of cotton and the marketing practices.
2. Establish pre-adoption socio-economic situation
The situation before the intervention relates to the production practices and the extent
of use of the various production practices, cotton yield and differences in gender roles
in seed cotton production
3. Document needs and constraints of cotton production and marketing
Capacity and development requirements of the cotton growers, constraints in cotton
production and marketing practices were identified.
4. Suggest solutions for addressing the identified constraints
Identify and document the opportunities that exist to address the constraints in cotton
production, and approaches for the most effective use of the identified constraints.
2.0 Methodology
2.1 The study Area
Cotton is grown in all provinces of Kenya except Nairobi, some of the major cotton growing
districts include Makueni, Kitui, Mwingi, Machakos, Mbeere, Tharaka and Meru North
districts in Eastern Province; Lamu, Taita Taveta, Malindi and Tana River in Coast Province;
and Baringo in the Rift Valley Province. In Kenya, cotton is largely produced under rain-fed
conditions by individual growers on landholdings of approximately one hectare, but the
number of farmers in each district varies from season to season (Ikiara and Ndirangu, 2002).
The project was implemented in 6 districts, which were selected based on production
potentials and farmers interest in growing cotton hence the likelihood of higher adoption and
62
impact. These districts were; Tharaka South, Kathonzweni and Kitui Central in Eastern
province, Lamu West and Tana Delta in Coast Province and Baringo North in the Rift Valley
Province.
2.1.1 Tharaka South District
Tharaka South district is one of the 52 districts in Eastern Province. It was created out of the
larger Tharaka district in the year 2009 and covers an area of 716.6 km2. The district borders
Meru Central and Imenti South districts to the west; Tigania, Igembe and Tharaka North
districts to the north; Mumoni District to the east and Meru South, Maara and Mbeere North
districts to the south. There are 5 administrative divisions namely; Tharaka Central, Nkondi,
Turima, Tharaka South and Tunyai, 14 locations and 33 sub-locations. The district has low,
hilly and sandy marginal low land. Its altitude lies between 500 and 900m asl. In most parts
of the district, soils are shallow, sandy and stony. The soils are characterized by the presence
of (a) Ferralsols- well drained, moderately to very deep, dusky red to red, friable clay found
around Nkondi and Tunyai Divisions; (b) Lithosols- well drained, shallow, stony and rocky,
friable to sand clay loam; and (c) Luvisols- well drained, moderately deep to deep, sandy clay
to clay.
The district experiences bimodal rainfall pattern ranging from 550 to 1,100 mm per year with
an annual average of 650mm. March–May is the first/long rains (with 34% reliability) while
the second/short rains are experienced in October–December (with 66% reliability).
Generally rains in Tharaka are fairly erratic and temperatures range between 29-36oC. The
average temperature of the area is 32oC and has very low humidity. Poor methods of farming
and soil conservation have left the earth bare and rocky while charcoal burning and over
grazing have contributed greatly to the current state of the landscape. There are three main
agro-ecological zones: (a) LM3 – Marginal cotton zone (25%) (b) LM4 – Lower midland
Livestock/Millet Zone (15%) and (c) LM5 / IL5 – Lowland livestock/millet zone – (60%).
The arable land accounts for 398.4km2 (55.6%) and non-arable land 174.2km2 (24.3%) while
144 km2 (20.1%) is forest land (with gazetted forest being 51.25 km2 and 92.75km2 is nongazetted forest). Average farm size (small scale) is 4.6Ha. Crop failure is frequently
experienced and this explains why less hectarage is put under crops. The district has a
population of 64,088 and 12,902 households with absolute poverty levels (rural and urban)
(1997) being 48.9%.
Farmers practice mixed farming though the lower parts of the district, which account for
slightly more than half of the district size, lean more towards livestock while the upper region
(about one-fourth of the total area) is more crop production oriented. Goats, sheep, chicken
and bees are the major livestock kept while cotton, green grams, sorghums and millets are the
main crops and attract traders to the district. The area currently under cotton production is
543 Ha. There has been a marked reduction in hectarage under cotton production (Table 1)
due to the failure of Meru ginnery in buying seed cotton from the farmers (2008/9) and with
the return of normal rains, majority of the farmers opted to plant subsistence crops.
63
Table 1: Cotton Production Trend in Tharaka South District
Year
2005
2006
2007 2008
2009
2010
Targeted ha
3,375
1,350 1,300
1,300
1,300
1,300
Achieved ha
1,136
936 1,350
850
851
543
Yield per ha (tonnes)
0.65
0.7
0.4
0.4
0.5
Target total production
2,700
1,080 1,040
1,040
1,040
1,040
(tonnes)
Achieved total production
738
655
540
340
396
(tonnes)
Source: MOA reports Tharaka South district
2.1.2 Kathonzweni District
Kathonzweni is in Eastern Province and was created from the larger Makueni district and
covers an area of 880.7km2. Arable land accounts for 781km2 and non-arable land 99.1km2.
The area experiences a bimodal rainfall pattern ranging from 200 to 600 mm per year and an
annual average of 400mm. March–May is the first/long rains season with a reliability of 34%
while the second/short rains season are experienced in October–December with a percent
reliability of 66%. Temperatures range from 20-28oC with very low humidity. The district
falls under two main agro-ecological zones: LM4 – Lower midland Livestock/Millet Zone
covering about 40% and LM5– Lowland livestock/millet zone covering about 60% of the
district. Its altitude lies between 700 and 1200m above sea level. Soils are mainly sandy,
loamy, clays and a few pockets of black cotton soils
It has a population of 82,243, 10,789 households, 8,223 farm families and an average farm
size of 3.54 ha. Farmers practice mixed farming. Cereal crops grown include maize, sorghum
and millets. Pulses mainly grown include bean, pigeon pea, cowpea and green gram. The
major industrial crops grown include; cotton, sunflower and sisal. They also grow fruits such
as citrus, mangoes, pawpaw’s guavas and watermelon. Other crops include; kale, tomatoes,
spinach, onions, cassava and sweet potatoes. Emerging crops includes Moringa, Jatropha and
Aloe vera. Farmers keep livestock – cattle, sheep, goat, and chicken mainly but guinea fowl,
doves, and fish are emerging as other livestock options.
Cotton is grown both as pure stand and is also intercropped with pigeon pea, green gram,
cowpea and bean. There are about 520 farmers growing cotton and 94 registered farmers
groups. Main challenges facing the cotton farmer include; poor farmer group organization,
high prices of pesticides, exploitation by middlemen, non gazettement of some cotton buying
centres such as Kithuki, Yinthungu, Yikiuku, Mwania, and Mbuvo, and inadequate road
infrastructure. Table 2 shows the cotton production trends in Kanthonzweni District for five
years.
Table 2: Cotton production trend in Kathonzweni District
Year
Target ha
Achieved ha
Target yield per ha (tonnes)
Achieved yield per ha (tonnes)
2005
2000
300
2
0.4
2006
2000
400
2
0.5
64
2007
1000
400
2
0.6
2008
3000
500
2
0.7
2009
1000
667
2
1.7
2010
2000
-
2.1.3 Kitui West District
Kitui West district is one of the 52 districts in Eastern Province which covers an area of
1087.2 km2. It has five administrative divisions namely Kisasi, Mbitini, Mbutsyani, Maliku
and Miambani. Of the total area, arable land accounts for 525.6 km2, rangeland 482.8km2,
79.8 km2 is forest land and total acreage under food crops being 16,800 km2. It has an average
land size of 1.18 ha. According to 1999 census, the district has a population of 193,200 and
32,400 households. The central part of the district is characterized by hilly ridges separated
by wide, low lying areas and has slightly lower elevation of between 600m and 900m above
sea level. To the eastern side of the district, the main feature is the Tiva River which forms
the boundary with Lower Yatta district. The district has a bimodal rainfall pattern, March–
May being the first/long rains, while the second/short rains are experienced in October–
December and are more reliable. The district experiences temperatures ranging from 130C to
340C during the year. The hot months, are February/March and September/October. The
minimum mean annual temperature is 15.70C and maximum mean annual temperature is
27.20C giving annual mean temperature of 21.4oC.
Cotton production in Kitui is basically rain-fed and planting is done during the short rains in
October/November. The main cotton producing regions in the district are Kisasi and Central
divisions. In 2009/2010, a total of 18 tons of cotton seed was distributed to farmers in the
larger Kitui district, 12 tons of which were for Kitui Central district alone. Currently about
1,950 hectares were planted during the short rains in 2009. Average seed cotton yields in
2008/2009 were about 300 Kg/Ha but the normal yields range from 350 – 420 Kg/Ha (Kitui
Central DAO Annual Report, 2009).
2.1.4 Lamu West District
Lamu West district was created from the larger Lamu district in 2009. It covers an area of
4,811.7 km2 out of which arable land is 4467.3km2. The district has 4 administrative
divisions, namely Mpeketoni, Amu, Hindi and Witu with a combined population of 67,704,
with 4232 households, 10,000 families and absolute poverty levels of 56%. The district has
sandy and clay loam soils comprising of low-lying land with the highest altitude of 50m asl.
It falls within four main agro-ecological zones: (a) Coastal Lowlands 3 (CL 3) –coconut/
cassava zone (571 km2), Coastal Lowlands 4 (CL 4) –cashewnut zone 3376 km2, (b) Coastal
Lowlands 5 (CL 5) –livestock/ millet zone 1606 km2and (c) Coastal Lowlands 6 (CL 6) ranching zone 24 km2. It has a binomial pattern of rainfall ranging from 540-1,100 mm per
year and an annual average of 650mm. The temperature ranges between 25-34oC with a mean
temperature of 27.9 oC and high humidity.
The main cash crops produced are: mangoes, cashew nuts, coconuts and ABE chillies while
the main food crops includes; maize, cowpea, green gram, and cassava. The main classes of
livestock are: goats, poultry, and local cows in the island and among pastoralists. The district
has an average farm size of 3.93 ha. The district has about 2,000 cotton farmers currently
with an average production of 0.7T per hectare. Cotton producing divisions are Mpeketoni
and Witu with 75% being produced from the later. Table 3 shows the cotton production
trends.
65
Table 3: Cotton production trends in Lamu West District
Year
2005
Achieved (Ha)
717
Achieved total production 700
(tonnes)
Source: MOA reports Lamu West district
2006
3244
3244
2007
2416
3624
2008
3613
3355
2009
3485
2680.1
2.1.5 Tana Delta District
Tana Delta district was created out of the larger Tana River district in the year 2008. It covers
an area of 16,013.4 km2 out of which 3822 is arable and 12,191.3 km2 is non-arable. The
district comprises of low-lying land with the highest altitude being 40m asl. The district has
bimodal rainfall pattern with an annual average of 900mm. Temperatures range between 2530oC with a mean temperature of 27 oC and high humidity. The district falls within four main
agro-ecological zones: (a) Coastal Lowlands 3 (CL 3) –coconut/cassava zone, Coastal
Lowlands 4 (CL 4) –cashewnut zone (b) Coastal Lowlands 5 (CL 5) –livestock/ millet zone
and (c) Coastal Lowlands 6 (CL 6) - ranching zone. The major soil types vary from sand to
sandy loam with some parts areas having pockets of clay soils. The district comprises of 3
administrative divisions namely Kipini, Tarasaa and Garseni. According to 1999 census, the
district had a population of 97,400 in 19300 households, with an average household size of 5
and a poverty index of 70%. The district has an average farm size of 0.39 ha. for small scale
farmers and 3.93 to 5.90 ha or large scale farmers. The main cash crops produced are:
coconut, cashewnut, mangoes, Bixa, cotton and simsim while the main food crops includes;
maize, cowpeas, green gram, cassava, rice and bananas. The main classes of livestock are:
African zebu, Galla goat, Small East African goat, Black headed Persian, Togenburg and
local poultry. The district has about 700 cotton farmers currently with an average production
of 0.5T per hectare (Table 4). The major cotton pests includes: aphids, cotton strainers,
cutworms, saw beetle and bollworms. Kipini division is the main cotton producing division in
the district. The cotton seeds are issued freely by the Government /Ministry of Agriculture as
a way of encouraging the farmers to grow the crop. Cotton is mainly planted as pure stand as
well as an intercrop. The main intercrops include; cotton with maize, cowpeas or green
grams.
Table 4: Cotton Production Trend in Tana Delta District for the last 5 years
Targeted ha
Achieved ha
Target yield per ha (tonnes)
Achieved yield per ha (tonnes)
Targeted total production (tonnes)
Achieved total production (tonnes)
No. of cotton farmers
Source: MOA reports Tana Delta district
2005
600
380
2006
700
480
2007
660
480
2
1.6
760
622
340
2
1.5
960
725
670
2
1.4
960
684
634
66
2008 2009
805
869
435
575
2
2.7
870
1170
623
2
2.2
1150
1280
536
2.1.6 Baringo North District
Baringo North district was created out of the larger Baringo District in 2008. The district
covers an area of 1693.5 km2 and comprises of Kabartonjo, Kipsaraman, Bartabwa and
Barwesa administrative divisions. The district lies in the unimodal rainfall area of the Rift
Valley region. Generally, the district lies in an altitude of between 600m and 1800m above
sea level. The major soil types are; clay loam, and loam, black cotton and red-silt soils plus
rocky areas. The district receives an average annual rainfall of 1,000 to 1,500mm and 600 to
800mm in the highlands and lowlands, respectively. In the lowlands, the reliability of the
rainfall exhibit a circle in which within four years, the area has one good year, two averages
(fair) years, and one dry year. The long-rains season usually starts in late March to early April
and ends in September while the short-rains season starts in October and ends in December
but, it is not consistent. The area has a mean temperature of 22oC.
According to the 1999 census, the district had a population of 78,529 people, 13,088
households with an average household size of 6 persons and a poverty index of 60%. There
are three main agro-ecological zones: upper midlands 3 (160km2), upper midlands 4
(240km2) and low midlands (1,293km2). Livestock keeping is an important economic
occupation of the farmers in the area. The estimated acreage under food crops in 2010 was
4,500ha with maize, sorghum, green grams and millet being the main food crops. Farmers
plant three types of cash crops; coffee, pyrethrum and cotton. Cotton is planted in MarchApril and takes about six months in the field from emergence to maturity. The arable land
suitable for cotton production is estimated to be 5,000ha where cotton is either grown in pure
stand or intercropped with either maize, cowpea or green gram. Cotton is grown in Kabutie,
Lawan, Kaboskei, Kerio locations of Barwesa division and Kinyech location, Bartabwa.
There is only one registered cotton farmers’ group in the district (Baringo North DAO,
Annual report, 2009). The area is served by Salawa Ginnery, located in Barwesa division.
2.1.7 Makindu District
Makindu district is one of the 52 districts in Eastern Province which covers an area of
848.2km2 of which 659 km2 is arable. It has a total population of 70,302 persons according to
the 2009 census results with a poverty level of 56%. The district has two rivers (Makindu and
Kiboko) which enable some irrigation producing both local and export vegetables. Cotton is
grown purely for cash purposes and it is grown in 4 clusters of the district which include
Twaandu location, Syumile in Ngumo location, Kyale in Kiboko location and Muuni in
Makindu Location.
2.1.8 Magarini District
Magarini district is one of the new administrative units in the Coast Province. It has a total
area of 2,416.8sq km and a population of 136,907 persons according to 2009 census and a
poverty level of 69%. The current area under the cotton crop is 230Ha with an average
production of 1 Ton per Ha. The potential production of cotton is 250 Ha and 2 Tons per ha.
The district has a bimodal rainfall pattern ranging from 200 to 600 mm per year and an
annual average of 400mm. March–May is the first/long rains season with a reliability of 34%
while the second/short rains season is experienced in October–December with a percent
reliability of 66%. Temperatures range from 20-28oC with very low humidity. The district
67
falls under two main agro-ecological zones: LM4 – Lower midland Livestock/Millet Zone
covering about 40% and LM5– Lowland livestock/millet zone covering about 60% of the
district. Its altitude lies between 700 and 1200m above sea level. Soils are mainly sandy,
loamy, clays and a few pockets of black cotton soils.
2.1.9 Baringo Central District
Baringo Central district is one of the 64 new administrative units in the Rift Valley Province.
It has a total area of 800.4sq km and a population of 89,174 persons according to 2009 census
with absolute poverty level of 37%. It is spread over 4 divisions of Salawa, Kabarnet, Sacho
and Tenges. Eighty percent of the district is semi-arid and the annual rainfall ranges between
600mm – 1500mm and an altitude range of 1500- 1700 m. The district has a high potential
for cotton production whereby 75% of area is suitable for cotton production. Cotton is grown
extensively in Salawa division and currently it is being introduced in Sacho and Tenges
Divisions which are also suitable for cotton production.
2.2 Data collection
The baseline survey was carried out between May 2010 and July 2010 for the project
implementing districts. The survey for the non-project districts was done a year later (MayJune 2011). Focus group discussions (FGDs) and household interviews were used to collect
primary data. In addition secondary data sources such as the District Agriculture Office
reports and other publications were used.
The District Agricultural Officer from each of the nine districts was advised to select the
major cotton value chain stakeholders at the district level who would constitute a forum for
the FGDs One focus group discussion was carried out in each project district involving 9-15
members drawn from the major cotton stakeholders. These included the district extension
officers of the Ministry of Agriculture, farmer representatives, ginners, marketing agents,
regulatory agents (CODA), research counterparts (KARI) and Non-Governmental
organizations (Table 5).
Table 5: Composition of Focus Group Discussions
Member Category
Farmer
representatives/KCGA
NGO’s
MoA/Co-op Officers
Cotton marketing agents
Financial service
providers
Ginner representative
CODA Officers
KARI Officers
Provincial
administration
Total
Tharaka
South
Kathon
zweni
Kitui
Central
Tana
Delta
5
4
4
5
5
2
2
2
-
2
4
1
1
3
1
-
3
2
-
1
3
-
1
2
-
1
1
2
-
15
15
12
Note: Districts marked with * are the comparison districts
68
Lamu
West
Baringo
North
Makindu
*
Magarini
*
5
1
4
Baringo
Central
*
2
3
2
-
2
-
3
3
-
3
3
-
3
-
2
1
-
2
1
-
3
2
-
1
1
1
2
1
1
2
1
1
13
13
12
10
14
9
3.0 Results and Discussions
3.1 Household Socioeconomic Characteristics
Over 70% of the respondents were household heads followed by spouses, with children
comprising a small percentage where the household heads were absent (Table 6).
Table 6: Relationship of the respondents to the household heads
Type of
respondent
Head
Spouse
Son
Daughter
Tharaka
South
29
(63.0%)
Kathonzweni
38
(86.4%)
Kitui
40
(83.3%)
Name of the District
Lamu
Tana
Baringo
West
Delta
North
36
38
40
(75.0%) (77.6%)
(83.3%)
5
(10.9%)
8
(17.4%)
4
(8.7%)
6
(13.6%)
0
(0%)
0
(0%)
8
(16.7%)
0
(0%)
0
(0%)
9
(18.8%)
1
(2.1%)
2
(4.2%)
8
(16.3%)
1
(2.0%)
2
(4.1%)
Makindu*
45
(90.0%)
Magarini*
34
(70.8%)
5
(10.0%)
0
(0.0%)
13
(27.1%)
1
(2.1%)
7
(14.6%)
1
(2.1%)
0
(0%)
Baringo
Central*
33
(66.0%)
17
(34.0%)
0
(0.0%)
Note: Districts marked with the * are the comparison districts
Majority of the households in the project districts were headed by males (>70%) while less
than 20% were headed by females; the same trend was observed in non-project areas.
Promotion of new cotton technologies and the subsequent adoption is therefore more likely to
be achieved if disseminated through the male population in the study area while not ignoring
the increasing number of female-headed households (Table 7).
Table 7: Gender of household heads in each district (%)
Gender
Male
Female
Tharaka
South
37
74.0%
13
26.0%
Kathonzweni
42
84.0%
8
16.0%
Lamu
West
39
78.0%
11
22.0%
Kitui
41
82.0%
9
18.0%
Tana
Delta
36
72.0%
14
28.0%
Baringo
North
42
84.0%
8
16.0%
Makindu*
44
(88.0%)
6
(12.0%)
Magarini*
40
(80.0%)
10
(20.0%)
Baringo
Central*
44
(88.0%)
6
(12.0%)
Note: Districts marked with the * are the comparison districts
The minimum age of household heads of the sampled households was 20 years (Table 8) and
maximum was 93 years with a mean of 50 years. The coastal districts had relatively younger
farmers growing cotton. This can be explained by the fact that the cotton growing zones in
Tana Delta and Lamu West were new settlement zones and most of the older generation was
not present in these areas.
Table 8: Age (in years) by gender of household heads (Standard error of mean in
brackets)
District
Tharaka South
Kathonzweni
Kitui
Lamu West
Tana Delta
Baringo North
Total (Beneficiary)
Mean
49(2)
56(1)
60(2)
49(2)
42(2)
49(2)
51(1)
Male
Max
93
77
89
70
65
76
93
Min
25
40
32
24
21
25
21
N
37
42
41
39
36
42
237
Mean
46(4)
42(4)
61(5)
44(5)
39(2)
42(4)
45(2)
69
Female
Max Min
72
25
54
30
80
29
72
20
53
25
55
25
80
20
N
13
8
9
11
14
8
63
Mean
48(2)
54(2)
60(2)
48(2)
41(2)
48(2)
50(1)
Max
93
77
89
72
65
76
93
Total
Min
25
30
29
20
21
25
20
N
50
50
50
50
50
50
300
Male
Mean
Max Min N
Makindu*
60 (2)
96
33
43
Magarini*
53(2)
86
26
40
Baringo Central*
49(1)
72
27
44
Total (non-beneficiary)
54(1.2)
96
26
127
Note: Districts marked with the * are the comparison districts
District
Mean
51
45(3)
35(2)
44(2.2)
Female
Max Min
61
37
60
34
44
26
61
26
N
6
10
6
22
Mean
59(2)
52 (2)
47 (1)
53 (1)
Max
96
86
72
96
Total
Min
33
26
26
26
N
49
50
50
149
Most of the household heads in the beneficiary districts had attained primary level of
education (53%), with non-formally educated including adult education consisting 18%.
Secondary and post-secondary education comprised approximately 26% and only 2% were
not educated (Table 9). A similar trend was observed for non-beneficiary districts. Given that
most households have attained some primary education it may mean that passing across
information on new or improved methods and technologies on farming systems is easier and
the level of understanding by the farmers is also higher. The level of education exhibited by
the cotton growers is low meaning that the transfer of improved crop production practices
could be better achieved using participatory approaches.
Table 9: Education profile of the household heads (%)
District
Tharaka South
Kathonzweni
Kitui
Lamu West
Tana River
Baringo North
Makindu*
Magarini*
Baringo
Central*
NonPrimary Secondary Postformal
secondary
22.4
42.9
30.6
4.1
16.0
54.0
30.0
38.0
48.0
10
4.0
78.0
8.0
10.0
4.0
16.3
46.9
34.7
2.0
22.0
49.0
14.0
14.0
18.0
64.0
18.0
30.0
54.0
10.0
6.0
8.0
62.0
28.0
2.0
Note: Districts marked with the * are the comparison districts
The main occupation of the household heads was farming (Over 70%) and the trend was
similar for both the beneficiary and the non-beneficiary districts (Table 10). This specifically
indicates that the study targeted the right clientele and these are the people that the
government is targeting to improve their livelihoods by promoting improved efficiency in
cotton production.
Table 10: Occupation profile of the household heads
Type of Occupation
Farmer
Business
Teacher
Government Employee
NGO employee
Farmer/Business
Farmer/Teacher
Farmer/Business/Govt
employee
Total Beneficiary Districts
Total Non-Beneficiary Districts
3
126
12
2
5
-
1
-
235
6
5
4
1
42
70
Type of Occupation
Pastor
Farmer/Government
employee
Masonry
Casual laborer
Total Beneficiary Districts
Total
Total Non-Beneficiary Districts
1
-
2
-
300
2
1
148
The mean household size was 7 and 8 members for the beneficiary and non-beneficiary
districts respectively (Table 11). Kathonzweni district had the highest number of household
members followed by Baringo North and Tharaka South districts. Baringo North had the
highest dependency ratio indicating that the number of those dependent on the household
farm for food and other requirements is high. Promotion of the cotton sub-sector could assist
such dependents especially with regard to employment. Magarini district had relatively
higher household size as compared to the others (Table 11).
Table 11: Average household size in the districts
District
Adult males in
the household
Tharaka South
Kathonzweni
Kitui Central
Lamu West
Tana Delta
Baringo North
Makindu*
Magarini*
Baringo Central*
Grand mean for all the districts
Adult females in
the household
3
4
1
2
1
2
3
3
3
Children under 18
years in the
household
3
3
1
1
1
2
2
3
2
Total
2
2
2
2
3
4
3
4
4
8
9
4
5
5
8
8
10
9
7
Note: Districts marked with the * are the comparison districts
The highest percentage of surveyed beneficiary households had semi-permanent family
houses (45%), while 38% had traditional houses with only a few owning permanent houses
(Table 12). This indicates that most of cotton producers are in low wealth category. Tana
Delta district had the highest number of households with traditional houses category; based
on this finding, and that the type of house is an indication of the wealth status of the farmer,
this district had also the highest poverty index (70%) among the six pilot districts. A similar
trend was observed for non-beneficiary districts with Magarini having more traditional
houses and a poverty level index of 69%.
Table 12: Type of houses owned by households
Type of house
Permanent
Semi-permanent
Total (Beneficiary)
44
(14.7%)
135
(45.0%)
71
Total (Non-Beneficiary)
9
(6.0%)
80
(53.7%)
Type of house
Traditional
Both semi-permanent &
traditional
Both permanent & semipermanent
Total
Total (Beneficiary)
115
(38.3%)
5
(1.7%)
1
(0.3%)
300
(100.0%)
Total (Non-Beneficiary)
60
(40.3%)
149
(100.0%)
The mean land size is 4.13 ha. for the beneficiary districts and 4.62 ha for the non-beneficiary
districts (Table 13). Few of the households rented land out to other users with only a mean of
0.28 ha; land rented in by households had a mean of only 0.16 ha. Kathonzweni district had
no cases of land leasing or renting as compared to other districts (Table 14). Forty five
percent of the households had freehold ownership of the land and possessed title deeds while
49% had individual pieces of land but without title deeds. Those who owned land
communally were only 3% and the other 3% had some of their land parcels with and without
title deeds. Land ownership is perceived as a sign of wealth and security by farmers, this is
also instrumental in credit acquisition especially for capital development on the farm.
Table 13: Average land size (ha.) owned by households
District
Tharaka South
Kathonzweni
Kitui
Lamu West
Tana Delta
Baringo North
Total beneficiary
Makindu*
Magarini*
Baringo Central*
Total non-beneficiary
Male
Mean
2.87
4.47
5.75
4.11
3.66
4.46
4.25
5.67
6.67
2.56
4.91
Female
Mean
1.89
5.02
5.39
3.82
4.19
2.36
3.70
4.26
3.07
1.38
2.93
Both male and female
Mean
2.62
4.56
5.69
4.05
3.81
4.12
4.13
5.50
5.94
2.42
4.62
Note: Districts marked with the * are the comparison districts
Table 14: Average land (ha.) rented in and out in the districts
District
Tharaka South
Kathonzweni
Kitui
Lamu West
Tana Delta
Baringo North
Makindu*
Magarini*
Baringo Central*
Land rented in
household (N=50)
Mean
by
Land rented out by
household (N=50)
Mean
0.16
0.00
0.36
0.15
0.11
0.22
0.17
0.13
0.20
0.29
0.00
0.10
0.25
0.47
0.62
0.31
0.13
0.18
Note: Districts marked with the * are the comparison districts
72
Table 15 indicates the status of land tenure in all the districts. Official land demarcation had
not taken place at all in Baringo North and some parts of Central whereas; in Tana Delta and
Tharaka South districts some areas had already been demarcated explaining why some of the
respondents owned title deeds. The late demarcation of these areas is probably due to their
marginalization.
Table 15: Type of land ownership by household
Individual
with title
Individual
without title
Communal
Both with and
without title deed
Total
Tharaka South
11
38
1
0
50
Kathonzweni
41
7
1
0
49
Kitui Central
41
5
2
1
49
Lamu West
33
12
2
3
50
Tana Delta
10
39
1
0
50
Baringo North
0
48
1
1
50
Makindu*
22
20
8
0
50
Magarini*
18
26
6
0
50
Baringo Central*
4
45
0
1
50
Name of the District
Note: Districts marked with the * are the comparison districts
Livestock ownership is an important indicator of household wealth. Indigenous chicken and
goats were the main types of livestock kept by households in the studied regions (Table 16).
Table 16: Average livestock ownership by households in beneficiary and nonbeneficiary districts
District
Tharaka South
Kathonzweni
Kitui
Lamu West
Tana Delta
Baringo North
Makindu*
Magarini*
Baringo Central*
Total: Beneficiary
Non-beneficiary
Cows
Oxen
Goats
Sheep
Chicken
Donkeys
2
5
2
1
2
7
1
2
5
3
3
1
2
1
0
0
6
1
0
1
2
1
4
9
7
12
8
24
8
6
11
11
8
3
2
0
1
1
9
1
1
5
3
2
11
21
21
18
22
7
10
11
11
17
11
0
1
1
0
0
0
1
0
0
0
0
Note: Districts marked with the * are the comparison districts
3.2.2 Cotton Production Characteristics
The minimum area for cotton production was 0.098 ha while the highest area under cotton
was 3.94 ha and 2.36 ha in beneficiary and non-beneficiary districts respectively. The mean
area under cotton was 0.76 ha and 0.57 ha for the beneficiary and non-beneficiary districts
(Table 17). The area devoted to cotton was lower than the average area under maize (main
staple crop) production which was 1.02 ha in project area and 1.10 ha in the non-beneficiary
districts. However, cotton was ranked first among the other crop enterprises in the project
districts and it was ranked second after maize in the non-beneficiary districts (Table 18 and
73
19). A total of 88 respondents said that cotton is their most important crop enterprise,
followed by maize (84 respondents) and green gram (57 respondents). This ranking of the
cotton enterprise differs with the FGD ranking where cotton enterprise was ranked number 2
in Kathonzweni and Lamu West districts, number 4 in Baringo North, number 7 in Kitui
Central and Tana Delta and number 8 in Tharaka South districts. A comparison of the annual
cotton yield for the year 2009 for the beneficiary districts revealed that Lamu West had the
highest annual yield followed by Tana Delta (Table 20).
Table 17: Average household cotton area (ha) in 2009 in project beneficiary and nonbeneficiary districts
Name of the district
N
Mean
Tharaka South
26
0.48
Kathonzweni
25
0.77
Kitui
25
1.05
Lamu West
33
0.82
Tana Delta
15
0.8
Baringo North
30
0.65
All beneficiary districts
154
0.76
Makindu*
28
0.52
Magarini*
26
0.7
Baringo Central*
45
0.53
All non-beneficiary districts
99
0.57
Note: Districts marked with the * are the comparison districts
Std Error of mean
0.13
0.2
0.43
0.34
0.26
0.2
0.12
0.14
0.28
0.17
0.12
Table 18: First ranked crop in beneficiary districts
Crop
Enterprise
Name of the District
Tharaka South
30
Kathonzweni
7
Maize
5
Millet
Cowpeas
9
Baringo North
3
Total
(N)
57
4
Lamu West
4
9
26
14
25
5
84
4
0
0
0
0
8
12
0
0
1
1
1
2
5
Sorghum
3
0
0
1
0
0
4
Pigeon peas
0
2
4
3
0
1
10
Cotton
6
30
5
8
12
27
88
Pawpaws
1
0
0
0
0
0
1
Beans
0
0
2
0
0
2
4
Mangoes
0
1
3
1
0
0
5
Cashew nut
0
0
0
10
0
0
10
Water melon
0
0
0
1
0
0
1
Ground nut
0
0
0
5
1
0
6
Simsim
0
0
0
1
1
0
2
Kales
0
0
0
0
1
0
1
Green gram
Kitui
Tana Delta
Dolichos
0
0
0
0
0
1
1
Total (N)
49
49
45
49
50
49
291
74
Table 19: First ranked crop in non-beneficiary districts
Name of the District
Baringo
Makindu Magarini
Central
21
1
8
8
35
13
0
0
5
2
0
1
0
0
2
19
13
16
0
0
3
0
1
0
0
0
1
0
0
1
50
50
50
Crop Enterprise
Greengram
Maize
Millet
Cowpeas
Sorghum
Cotton
Beans
Tomatoes
Watermelon
Boma rhodes grass
Total
Total
N
30
56
5
3
2
48
3
1
1
1
150
The average cotton yield per Ha in the project area was 869kg (Table 20) which is mid-way
from documented farmer yields of 572kg/ha (CODA, 2009) and the potential yield of
2500kg/ha whereas in the non-beneficiary districts, the yield was equivalent to documented
farmer yields. The variances in yields can be attributed to a combination of factors mainly
climatic conditions, for instance Baringo central receives relatively higher rainfall amounts as
compared to Makindu district. The yield differences in areas with same agro-ecological zones
indicate that there is potential for increasing productivity in areas with low productivity. It is
also possible to increase productivity in all the cotton growing areas given good production
practices and the availability of the necessary inputs and appropriate marketing practices.
Table 20: Average cotton yield in kilograms per ha in project beneficiary and nonbeneficiary districts.
N
Total Area (ha.)
Total production (kg)
Tharaka South
Kathonzweni
Kitui Central
Lamu West
Tana Delta
Baringo North
Makindu*
Magarini*
Baringo Central*
Total beneficiary
26
25
25
33
15
30
28
26
45
154
12.62
19.5
26.8
27.5
12.2
19.7
14.92
18.6
24.1
118.32
6390
11520
11103
46440
14350
13050
4775
8410
19782.15
102853
Average yield in
kg/ha
506.3
590.8
414.3
1688.7
1176.2
662.4
320.04
452.15
820.84
869.3
Total Non-beneficiary
99
57.62
32967.15
572.15
Name of the District
Note: Districts marked with the * are the comparison districts
It was found that there was minimal mechanization in carrying out the various operations like
weeding and harvesting in the production of cotton (Table 21). This may be due to low
resource base of the cotton growers, which could be alleviated by facilitating farmer access to
financial services (e.g. credit services) and or pooling of resources by the cotton growers.
Spraying against pests and diseases was mainly done using a knapsack sprayer and it was
mainly done by men. It was a common phenomenon for all cotton farm production activities
75
to be done by all members of the household including boys and girls in the range of 7 to 18
years. Most respondents complained that cotton production was labour intensive because
most activities were done manually as indicated in Table 21. Most of the interviewed farmers
were not aware of the variety of cotton seed that they plant. Those who had knowledge of the
varieties they planted knew of two varieties, namely Hart 89M and KSA 81M. This indicates
limited farmer access to information and hence a need for a system that allows access to
information. In this case the extension system may consider production of information in
different formats and make it available to the cotton growers. Along the same lines CODA
and KARI need to participate in the information dissemination processes.
There was also low mechanization of cotton production in the non-beneficiary districts.
Transportation of cotton from the farm or to the market was done in various ways. The most
commonly used means of transportation was bicycle followed by head/back load and then
vehicles. Other means of transportation mentioned included carts and wheelbarrows.
Table 21: Use of various production activities in project beneficiary and non-beneficiary
districts
Activity
Land preparation
Planting
Weeding
Spraying
Harvesting
Transportation
Total
Hand
106
219
243
61
271
40
940
Oxen
53
50
14
1
10
128
Number of responses
Tractor
Knapsack sprayer
90
6
1
234
18
115
234
Pesticide application was found to be the major method of controlling or preventing cotton
pests and diseases by the farmers. Most farmers had the knowledge of various pesticides with
most using Bulldock, Bestox, Polytrin and Karate in the beneficiary districts. Pesticides used
in the non-beneficiary districts in order of frequency included Polytrin, Cyclone, Bulldock,
Karate, Bestox and Robust. Results from the survey indicated minimum fertilizer application
in cotton production. Twenty three percent of the farmers in beneficiary districts indicated
having used the different types of inorganic fertilizers, which included foliar sprays. A few
(18%) reported having used farm yard manure. There was similar tendency in the nonbeneficiary districts. There was minimal herbicide use in cotton production for both areas.
Cotton ratooning (cutting cotton stems at the ground level and allowing them to sprout) was
not a common practice in the sampled regions with only 14% and 24% of the households
indicating having done the practice in beneficiary and non-beneficiary districts respectively.
At least 50% of those who practice cotton ratooning do it to increase yields and ensure faster
growth of the crop (Table 22). In the non-beneficiary districts, ratooning to fetch a higher
price since ratoon crop is harvested earlier was stated as one of the major reasons.
76
Table 22: Reasons for cotton ratooning in project beneficiary districts
Reasons for cotton ratooning
Number of responses
To improve production/yields
14 (33%)
Due to lack of seeds
6 (14%)
Faster growth of the crop
10 (24%)
Unreliable rainfall
1 (2%)
To save planting labour
7 (17%)
Both to improve soil fertility and production/yields
1 (2%)
To save on pesticides cost
3 (7%)
Total (n)
42 (100%)
Note: values in parentheses refer to per cent of the total responses
Crop rotation was practiced by most of the cotton producers (63% for beneficiary, 64% for
non-beneficiary) but it was ad hoc since they did not have a well-defined rotation. The major
reasons given for practicing crop rotation were to control pests and diseases, to improve soil
fertility and to increase cotton productivity.
Only 73 farmers in the sample from the project beneficiary districts produced cotton under
contract arrangement indicating that contract farming in cotton production was not common
(Table 23). It was most common in Baringo North and Central Districts due to the existence
of a private ginner (Salawa ginnery) who made some contract arrangements with cotton
producers. Also the numbers in Kitui and Lamu West could be due to the recent contract
cotton seed production in those areas. The main contract agreements were ploughing of land,
provision of pesticides and seeds on credit for farmers to pay after selling their seed cotton.
Table 231: Contract arrangements for cotton production in beneficiary districts
Name of the District
Tharaka South
Have you ever produced cotton under contract
arrangement?
Yes
No
0
48
Total
48
Kathonzweni
4
46
50
Kitui
15
35
50
Lamu West
16
34
50
Tana Delta
2
48
50
Baringo North
36
14
50
Makindu*
22
28
50
Magarini*
1
47
48
Baringo Central*
47
3
50
Note: Districts marked with the * are the comparison districts
Most farmers grade the cotton after harvesting (Table 24).
77
Table 24: Grading of cotton at farm level in project beneficiary and non-beneficiary
districts (%)
Sorting of cotton
Percent (beneficiary
Percent (Non-beneficiary
districts)
districts)
During harvesting
36.7
20.0
After harvesting
40.0
72.7
Both
during
and
after
9.0
harvesting
Do not sort
14.0
7.3
Missing value
0.3
Total
100.0
100.0
Less sorting is practiced in the coastal districts as compared to the other upland districts
(Table 25). This can be explained by the fact that the quality of the seed cotton is better in
the coastal districts because the cotton crop takes shorter time in the field with only one rainy
season as compared to the Eastern districts. It could also mean that the infestation of the
cotton crop by pests such as cotton stainers is lesser in the coastal areas.
Table 25: Cotton grading in project beneficiary districts
District
During harvesting
After harvesting
Tharaka South
37
12.4%
6
2.0%
Both during and after
harvesting
7
2.3%
Kathonzweni
21
7.0%
23
7.7%
5
1.7%
1
.3%
Kitui
20
6.7%
23
7.7%
7
2.3%
0
.0%
Lamu West
9
3.0%
24
8.0%
0
.0%
17
5.7%
Tana Delta
13
4.3%
13
4.3%
1
.3%
23
7.7%
Baringo North
10
3.3%
31
10.4%
7
2.3%
1
.3%
Do not sort
0
.0%
Most of the farmers reported that cotton seed is supplied to them by the Ministry of
Agriculture and ginneries (85% and 71% for beneficiary and non-beneficiary districts
respectively). Seventy eight percent reported that the seed was available on time for planting
while only 22% said that seed was not available on time in beneficiary districts. Tharaka
South district had the highest instances of delayed supply of seed (Table 26). This could be
attributed probably to the poor infrastructure of the area and inefficient local ginnery
operations. In the non-beneficiary districts, eight one percent of the farmers said that the seed
was available on time for planting while the remainder said that seed was not available
timely. Magarini district had the highest instances of delayed seed supply which could also be
attributed to the poor infrastructure of the area (Table 27).
78
Table 26: Source of cotton seeds and their availability in the beneficiary districts
MoA
District
Available
on time
Tharaka
16
South
25.8%
Kathonzweni 3
4.8%
Kitui
0
.0%
Lamu West
28
45.2%
Tana Delta
15
24.2%
Baringo
0
North
.0%
Late
7
38.9%
2
11.1%
1
5.6%
4
22.2%
4
22.2%
0
.0%
Ginnery
Available
on time
11
8.5%
33
25.6%
32
24.8%
6
4.7%
13
10.1%
34
26.4%
Late
4
14.3%
0
.0%
5
17.9%
10
35.7%
4
14.3%
5
17.9%
Supplier/source of seed*
MoA & Ginnery
Other
Available
Available
on time
Late
on time
3
1
1
20.0%
20.0% 3.7%
1
0
11
6.7%
.0%
40.7%
4
3
2
26.7%
60.0% 7.4%
0
0
2
.0%
.0%
7.4%
4
1
5
26.7%
20.0% 18.5%
3
0
6
20.0%
.0%
22.2%
Late
6
46.2%
0
.0%
1
7.7%
0
.0%
4
30.8%
2
15.4%
Total
Available
on time
31
13.3%
48
20.6%
38
16.3%
36
15.5%
37
15.9%
43
18.5%
Late
18
28.1%
2
3.1%
10
15.6%
14
21.9%
13
20.3%
7
10.9%
* Percent in brackets
Table 27: Source of cotton seeds and their availability in the non-beneficiary districts
District
Supplier/source of seed
Chief
Others1
MoA
Ginnery
Total
Available
on time
Late
Available
on time
Late
Available
on time
Late
Available
on time
Late
Available
on time
Late
Makindu 17
Magarini 12
0
10
10
3
1
3
7
10
3
6
9
5
3
1
43
30
7
20
Baringo
Central
Total
1
1
47
1
0
0
0
0
48
2
30
11
60
5
17
9
14
4
121
80.7%
29
19.3%
1
Others are brokers/buying agents, co-op society and neighbours
Cotton Production Situation
Most of the farmers interviewed (81% for beneficiary and 85% for non-beneficiary districts)
had a cotton crop in their farms at the time of the survey. The mean area under cotton during
the period of the survey were 0.76 ha ranging from an average of 0.65 ha in Baringo North to
0.82 ha in Lamu West for beneficiary districts with a minimum of 0.10 and a maximum of
4.33 ha. Lamu West, Kitui Central and Kathonzweni districts had the highest areas under the
cotton crop during the survey period. This indicates that farmers in these areas were more
serious in cotton production given the efforts by the government through CODA and other
agencies to encourage farmers to grow cotton. Average area for the non-beneficiary districts
was 0.57 ha ranging from 0.53 ha in Baringo central to 0.70 ha in Magarini with a minimum
of 0.19 and a maximum of 2.34 ha.
In the study period, more farmers intercropped cotton as opposed to planting pure stand
compared to previous seasons (Table 28).
79
Table 28: Cotton production systems in beneficiary and non-beneficiary districts
System of production
Pure stand
Intercropping
Both
Total
1
Beneficiary districts
2
Non-beneficiary districts
Frequencies
Current season
Previous seasons
(2009/2010)1 (2010/2011)2 (1972-2009)1
93 (38%)
47 (36%)
133 (48%)
127 (51%)
82 (62%)
124 (45%)
27 (11%)
3 (2%)
21 (7%)
247 (100%) 132 (100%) 278 (100%)
(1985-2010)2
45 (32%)
95(66%)
3 (2%)
143 (100%)
Tharaka South, Kitui Central and Lamu West districts commonly intercropped the cotton.
Pure stand cropping system was more common in Baringo North and Kathonzweni and same
case applied to Magarini and Baringo Central districts. It is also important to note that pure
stand cropping system was mainly practiced before liberalization of the sector and vice versa
for intercropping. This is because the Cotton Board of Kenya which was previously
controlling the sub sector had discouraged intercropping and also as income from the cotton
had been more favourable according to farmers. The major reasons that farmers gave as to
why they practice pure stand cropping were to maximize yields, to reduce pest attack and to
ensure good quality cotton production. The major reasons given for practicing intercropping
were to economize on land, diversification to include food crops, to increase productivity per
unit area and to improve soil fertility.
3.2.2.1 Constraints to Cotton Production
In the beneficiary districts, low seed cotton price was ranked as most serious constraint to
cotton production (by at least 86.7% of the farmers). This was followed by pest problems
(cotton stainers and bollworm) and then high cost of pesticides, aphids and inadequate
implements (Table 29) for the beneficiary districts. In the non- beneficiary districts, bollworm
was ranked as most serious constraint (at least 76% of the farmers. This was followed by
inadequate farm implements and cotton stainers (another pest) coupled with low prices,
aphids and red spider mite. These serious pest and other constraints have led many farmers
to abandon cotton production in Kenya but cotton production was once a thriving sub-sector
in the country.
80
Table 29: Prioritization of constraints in cotton production in project beneficiary and
non-beneficiary districts
Constraint
Beneficiary districts
% of total population
N
N
Non-beneficiary districts
% of total population
Low Prices
260
86.7
99
67
Cotton stainers
196
65.3
105
71
Bollworm
183
61.0
126
86
High Cost of Pesticides
177
59.0
49
33
Aphids
170
56.7
79
54
Inadequate implements
104
34.7
112
76
Delayed payments
93
31
Lack of spray pumps
92
30.7
Red spider mites
85
28.3
73
50
Insufficient capital
10
28.0
Lack of transport
67
22.3
53
36
Poor pesticide availability
58
19.3
Lack of market information
50
16.7
46
31
High cost of transport
48
33
Poor storage
43
29
i) Disease/Pest related constraints
Bollworms, cotton stainers, cotton aphids, red spider mites and white flies were the highest
ranked pest/disease constraints in all the districts (Table 30). This confirms the importance of
the bollworm in cotton production which has led most of the cotton producing countries in
the world to adopt the Bt cotton. Cotton stainer was also found to be of high economic
importance in the study areas.
Table 30: Important pest/disease related constraints to cotton production in project
beneficiary and non-beneficiary districts
Type of pest/disease
related constraint
Bollworm
Beneficiary districts
N
Percent of cases
208
71.5%
Non-beneficiary districts
N
Percent of cases
128
85%
Cotton stainers
206
70.8%
110
73%
Cotton Aphids
193
66.3%
81
54%
50%
Red spider mites
95
32.6%
75
White flies
21
7.2%
32
21.3%
20
13.3%
Armyworms
10
6.7%
Leaf rot
7
5%
Cutworm
18
6.2%
Cotton scales
15
5.2%
Cotton rust
14
4.8%
Stinging bug
13
4.5%
Wild life menace
11
3.8%
Curling of leaves
11
3.8%
Beetles
10
3.4%
81
ii) Inputs, equipment, weather and ecology constraints for cotton
production
Most constraints under this category mainly related to lack of capital. The constraints
included high cost of pesticides, inadequate implements e.g. spraying pumps, oxen ploughs
and hoes and poor access to inorganic fertilizers and seeds among others (Table 31). Farmers
reported that there were priority pests and diseases that affect productivity and with low
capital, purchase of pesticides and other improved inputs might lead to loss making on the
part of the farmer, while not using the inputs also results in low quality cotton that may not be
absorbed in the market.
Table 31: Inputs, equipment, weather/ecology constraints to cotton production in
project beneficiary and non-beneficiary districts
Type of Input/Equipment/Ecology
Constraint
High cost of pesticides
Beneficiary districts
N
Percent of Cases
175
59.1%
Non-beneficiary districts
N
Percent of Cases
51
35%
114
78%
Inadequate farm implements
116
39.2%
Lack of Spraying pumps
103
34.8%
Insufficient capital
87
29.4%
14
9.6%
15
10.3%
31
21%
Inadequate fertilizers (Inorganic)
54
18.2%
Inadequate labour
42
14.2%
Untimely seed supply
40
13.5%
Unreliable/Poorly distributed Rainfall
33
11.1%
Ineffective pesticides
31
10.5%
Poor pesticide availability
29
9.8%
Lack of herbicides
26
8.8%
Lack of gunny bags
20
6.8%
Inadequate manure
18
6.1%
Poor Quality Seeds
17
5.7%
20
14%
Expensive fertilizers
15
5.1%
17
12%
Lack of enough seed
14
4.7%
33
23%
High cost of labour
11
3.7%
11
7.5%
7.5%
11%
Lack of protective clothing when spraying
11
3.7%
11
Lack of enough tractors
9
3.0%
16
iii)
Marketing related constraints
Low prices of seed cotton were the biggest hindrance to cotton production in all six districts
sampled. Delayed payments, inadequate transport, and lack of market information were other
major constraints that were mentioned. Table 32 denotes that there was a total collapse of the
seed cotton marketing system due to the defunct Cotton Lint and Seed Marketing Board.
82
Table 32: Priority marketing related constraints to cotton production in project
beneficiary and non-beneficiary districts
Low prices
Delayed Payment
Lack of transportation
Lack of market information
Brokers Exploitation
Beneficiary districts
N
Percent of Cases
268
91.2%
105
35.7%
87
29.6%
65
22.1%
47
16.0%
Poor storage facilities
Unreliable markets
Problems with the weighing machines
39
15
11
13.3%
5.1%
3.7%
Buying centre being far
11
3.7%
Delay in buying of the cotton
High cost of transport
Long distance to markets
9
3.1%
Type of Market related Constraint
Non-beneficiary districts
N
Percent of Cases
101
67.8%
21
14%
57
29.6%
46
31%
14
9.4%
48
17
32.2%
11.4%
Farmers Interventions against the constraints to cotton production
The major intervention against pests and diseases was chemical control. However, a third of
the respondents in each region indicated that they had used no interventions against the
various pest/disease constraints. The high cost of inputs and equipment was offset by sale of
livestock and other farm produce to procure the necessary inputs and they also relied on
neighbours by borrowing or hiring because of the issue of low cotton prices , most farmers
said that they had no control over marketing issues so could make no interventions.
Farmers’ suggestions to improve cotton productivity
Given the challenges that they were facing in the sub-sector, farmers suggested various
options to increase seed cotton productivity (yield per ha) These included, improvement of
prices, adoption of good agronomic practices, provision of loans or credit to farmers and
training of farmers on cotton value chain issues (Table 33 & 34). These findings concur with
the FGD results whereby increases in seed cotton prices; more training of farmers on good
agronomic practices including timely pests control and fertilizer application; use of high
yielding varieties and provision of loans or credit to farmer and input subsidies from
government were also reported during the discussions.
83
Table 33: Farmer suggestions on how to improve cotton productivity (project districts)
Responses
Farmers suggestions
N
Percent of Cases
Improve cotton prices
33
11.0%
Provide loans/credit to farmers
32
10.7%
31
10.3%
29
9.7%
Use & application of farm yard manure
29
9.7%
Use of fertilizers
28
9.3%
Practice regular spraying
28
9.3%
Practice early planting
26
8.7%
Practice timely pest control
25
8.3%
Provide farmers with inputs/pesticides
23
7.7%
Plant high yielding cotton varieties
22
7.3%
Practice early land preparation methods
17
5.7%
Provide good quality of pesticides to farmers
16
5.3%
Practice early weeding
16
5.3%
Practice crop rotation in order to yield more
15
5.0%
Farm visits by extension workers
15
5.0%
Provide good quality of seeds
14
4.7%
Subsidize cotton farm inputs
14
4.7%
Use of appropriate chemicals
13
4.3%
Train farmers on cotton production through
seminars
Plant cotton as a pure stand
Table 34: Farmers suggestions on how to improve cotton productivity (non-project
districts)
Farmers suggestions on productivity
Good agronomic practices
Provide farmers with advice on chemicals to use
Provide farmers with pesticides & insecticides
Advice on new farming methods
Plant high quality of seeds
Improve on cotton prices
Provision of farm inputs & implements
Advice on water conservation techniques
Farmers training on cotton production
Provide farmers with loans
N
75
34
32
19
19
16
13
11
9
6
Percent of Cases
50%
22.7%
21.3%
12.7%
12.7%
10.7%
8.7%
7.3%
6.0%
4.0%
Credit Issues in Cotton Production Chain
Seventy five percent of the respondents from beneficiary and 35% from non-beneficiary
districts indicated that they obtained funds for cotton production from the sale of other farm
enterprise products. Other farmers had a combination of various sources of funds which
included own businesses, salary or wages, remittances. Also 5% and 17% from beneficiary
and non-beneficiary districts respectively, sourced from ginneries. Credit acquisition was
very rare among the sampled farmers with only 5% of the respondents obtaining credit in the
year 2009 and 2010 for the beneficiary districts (Table 35). The source of the credit was
mainly ginneries and two respondents received the credit from Equity and Kenya
84
Commercial Banks mainly for the purposes land preparation and input acquisition. In the
non-beneficiary districts only one respondent had acquired credit in the last five years.
Table 35: Credit Acquisition
Year
2009
2009
2010
2010
Amount
in Frequency
KSH
1,500- 21,000
8
19,000
1
2,500 – 2,860
4
100,000
1
Source
Purpose
Ginnery
Equity Bank
Ginnery
KCB
Land preparation
Farm Inputs
Land preparation/spraying
Farming
In the beneficiary districts, the problems said to be associated with credit acquisition were
mainly lack of information on how and where to access the loan (29%) and lack of the ability
to repay the loan (18%). The constraints associated with credit repayment included high
interest rates (42 %) and unreliable weather (17%). To improve the cotton grower access to
credit facilities it will be necessary to increase farmer access to information about credit
facilities available as well as the terms and conditions of credit.
In the non-beneficiary districts, the problems said to be associated with credit acquisition
were mainly lack of collateral including title deeds and lack of awareness on the existence of
any credit facilities. The constraints associated with credit repayment as implied by the
farmers were mainly the risks and uncertainties involved in agriculture and high interest rates.
Other Cotton Development Programs in the Study Area
There was evidence of other development programs to tackle cotton production issues in the
sampled area. These included Non-Governmental Organizations (NGO’s) like Christian
Community Services (CCS) and Mount Kenya East Pilot Project (MKEPP) in Tharaka South,
Business Initiatives for Survival and Eradication of Poverty (BISEPS) in Kitui Central and
World Vision in Magarini. Others included private companies especially agro-chemical
companies who were training or demonstrating to farmers on use of the various chemicals to
control pests and diseases in cotton. However, 38% and 40% of the respondents in
beneficiary and non-beneficiary districts respectively, said that they were not aware of the
existence of any cotton development programmes in their vicinity.
Sources of advice on improved cotton farming practices
Cotton farmers have various sources of information on improved cotton farming practices.
Extension advice featured prominently among others (Table 36). This can be attributed to the
efforts of the government to promote the sub sector by use of the Ministry of Agriculture
extension staff in recent years. Farmer to farmer exchange (neighbours) of information was
found to be very important. This means this avenue if used in addition to the formal extension
service can play a vital role in promotion of the cotton sub sector. Lamu West and Baringo
North districts had relatively higher number of respondents who do not receive information
from any source. A similar trend was indicated in the non-beneficiary districts. In addition,
Magarini and Makindu districts had relatively higher number of respondents who had not
received information from any source.
85
Types of advice received included training on cotton crop agronomic management practices,
proper use of chemicals and how to dispose them and other farming technologies and more so
importance of growing cotton.
Table 36: Sources of information on better cotton farming practices
Source of
advice
Extension officers
Neighbours
NGOs
Private company
None
Extension
officers/NGO's
Extension
officers/Neighbours
Neighbours/NGO's
Extension
officers/private
company
Own advice
Ginnery field officers
Total
No.&
%
Tharaka
South
Kathonzweni
Kitui
Central
Lamu
West
Tana
Delta
Baringo
North
Count
%
Total
Count
%
Total
Count
%
Total
Count
%
Total
Count
%
Total
Count
%
Total
Count
%
Total
Count
%
Total
Count
%
Total
of
28
9.4%
18
6.1%
29
9.8%
31
10.4%
38
12.8%
33
11.1%
177
59.6%
of
4
1.3%
20
6.7%
6
2.0%
3
1.0%
4
1.3%
0
.0%
37
12.5%
of
0
.0%
1
.3%
1
.3%
0
.0%
0
.0%
0
.0%
2
.7%
of
0
.0%
0
.0%
3
1.0%
0
.0%
1
.3%
0
.0%
4
1.3%
of
4
1.3%
2
.7%
1
.3%
13
4.4%
4
1.3%
9
3.0%
33
11.1%
of
9
3.0%
1
.3%
3
1.0%
0
.0%
1
.3%
0
.0%
14
4.7%
of
5
1.7%
8
2.7%
2
.7%
0
.0%
1
.3%
7
2.4%
23
7.7%
of
0
.0%
0
.0%
1
.3%
0
.0%
0
.0%
0
.0%
1
.3%
of
0
.0%
0
.0%
3
1.0%
0
.0%
0
.0%
0
.0%
3
1.0%
Count
%
of
Total
Count
%
of
Total
Count
0
.0%
0
.0%
0
.0%
1
.3%
1
.3%
0
.0%
2
.7%
0
.0%
0
.0%
0
.0%
0
.0%
0
.0%
1
.3%
1
.3%
50
50
49
48
50
50
297
%
Total
16.8%
16.8%
16.5%
16.2
%
16.8
%
16.8%
100.0
%
of
Total
COTTON MARKETING
Market Outlets
Ginneries are very important to the seed cotton production chain. This is because they are
supposed to buy the seed cotton from the producers and then gin to produce the cotton seed
and lint. Farmers were asked whether they had knowledge of any functional or non-functional
ginneries in their areas. The main functional ginneries during that period are as indicated in
Table 37.
86
Table 37: Farmers awareness of functional ginneries in project beneficiary and nonbeneficiary districts
Ginnery
Gaitu
Kitui
Gaitu &
Kitui
Do not
know
None
Tunyai,
Gaitu &
Kitui
Gaitu &
Tunyai
Mitunguu
Ginnery
Gaitu,Kitui
and Mwea
Tharaka
Ginnery
Meru
ginnery
Gaitu &
Meru
Ginnery
Makueni
T.S.S
Tharaka
South
10
Tana
Delta
0
Baringo
North
0
Magarini*
Kitui
0
Lamu
West
0
Makindu*
Kathonzweni
0
0
2
0
49
4
1
0
11
0
0
0
0
0
11
0
1
3
3
0
7
0
0
3
1
0
1
0
0
0
0
0
1
0
0
0
0
0
2
0
0
0
0
0
0
Baringo
Central*
0
Total
10
0
0
0
56
0
0
0
0
0
0
3
1
0
0
0
0
11
18
15
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
1
0
0
0
0
0
1
0
0
0
0
0
2
0
0
0
0
0
1
0
0
0
0
0
0
50
0
0
0
0
47
0
0
97
0
0
0
13
20
0
0
0
0
33
1
0
39
1
1
2
1
Mpeketoni
0
0
0
25
13
0
0
Malindi
0
0
0
0
5
0
0
48
0
53
0
0
1
Mkombozi
0
0
0
0
1
0
0
Lamu
0
0
0
0
6
0
0
0
0
6
50
0
0
50
100
Salawa
0
0
0
0
0
Note: Districts marked with the * are the comparison districts
The ginneries that farmers indicated they were not operational were mainly Tunyai ginnery in
Tharaka South and Mpeketoni and Lamu Ginneries in Lamu West district. The respondents in
Makindu and Baringo Central were not aware of any non-functional ginneries in their region
but in Magarini district some indicated that the Marikebuni ginnery was not functioning.
Apart from ginning, ginneries provide other services but 43.3% and 52% of the respondents
in beneficiary and non-beneficiary districts respectively indicated that they do not receive any
other benefits from the ginneries. However, those who do receive other benefits gave the
following major ways in which they benefit from ginneries (Table 38).
87
Table 38: Farmers awareness of other benefits from ginneries in project beneficiary and
non-beneficiary districts
Beneficiary Districts
Percent of
N
Cases
Non-beneficiary districts
Percent of
N
Cases
Type of Benefit
Provision of seeds
126
42.3%
33
22.3%
Buying cotton from farmers
34
11.4 %
13
8.8%
28
9.4%
12
4.0%
11
3.7%
8
2.7%
17
11.5%
5
1.7%
6
2%
25
16.9%
16
10.8%
77
52.0%
Provide farmers with pesticides on credit
Provide gunny bags
Collects produce from the buying centre
Renders tractor services/ploughing to the farmers
Advising of farmers
Create job opportunities/improve community
livelihoods
Provision of farm equipment/inputs
None
129
43.3%
Distance to Markets
The average distance to the buying centres in the beneficiary districts was 6.8 km (N=269)
with a maximum of 57 km and a standard deviation of 12.3. The minimum was 0km which
meant that the cotton was bought at the farm gate level by either middlemen or ginners. The
average distance for the non-beneficiary districts was 12.6 km with highest being 60 km and
minimum of 0.4km and a standard deviation of 17.2. The distances in non-beneficiary
indicate that the farmers took their cotton to the buying centres as opposed to earlier times
when agents could acquire the cotton at farm gate level.
Buyers of Seed Cotton
The buyers of seed cotton were mainly the ginners (46%) followed by buying agents or
middlemen (45%) in the beneficiary districts. In Baringo North and Kitui Central districts
buyers of seed cotton were the ginners. The use of buying agents or middlemen was more
common in Tharaka South and Tana Delta Districts. Lamu West and Kathonzweni districts
used these two kinds of buyers but in addition a cooperative society was buying seed cotton
in Kathonzweni.
In the non-beneficiary districts, the buyers of seed cotton were mainly the ginners (92%)
followed by buying agents or middlemen (7%) and one respondent from Makindu district
stated that a cooperative society was the buyer. In Baringo Central and Magarini districts it
was purely the ginner who was buying cotton.
On the issue of other roles that are played by the seed cotton buyers, 49% and 40% of the
respondents in beneficiary and non-beneficiary districts respectively indicated that they do
not receive any other role from them. However, some indicated that the buyers provided
seeds, transport, Ploughing services, pesticides and other inputs on credit among other roles.
88
Most farmers (43%) indicated that price is the major determining factor of where or whom to
sell their seed cotton to for the beneficiary districts. Others stated that they had knowledge of
only one buyer and that is where they sold to whereas some (6%) said that they had no choice
of where to sell. Other reasons given as determining factors included prompt payment, first
come basis, influence by opinion leaders like the chairman of cotton growers association and
provision of transport by the buyer.
In the non-beneficiary districts, most farmers indicated that availability of the buyer, price
and agreements with the buyer were the major determining factors of where or whom to sell
their seed cotton to. Most stated that they had knowledge of only one buyer and that is where
they sold.
Average farm gate prices
The farm gate price of the AR grade of cotton ranged from 20-28 shillings per kg in the
beneficiary districts. The mode was KSH. 26 per kg for the 2009 and it was mostly used in
Baringo North district. Few respondents (4) gave a price range of 11 to 17 shillings for the
BR grade of cotton.
In the non-beneficiary districts, the average farm gate price of the AR grade of cotton was 31
shillings per kg with the highest in the region being Ksh. 50 per kg. The average price for the
BR grade was Ksh.16 per kg with the highest being Ksh. 19 per kg.
Farmers Suggestions on Improving Cotton Marketing
Table 39 indicates the major suggestions from the farmers on what could be done to improve
the cotton markets. The price improvement was found to be the major driving factor for
production of cotton.
Table 39: Farmers suggestion to improve cotton marketing in project beneficiary and
non-beneficiary districts
Suggestions
Beneficiary
Percent of
Cases
121
40.7%
43
14.5%
33
11.1%
22
7.4%
21
7.1%
17
5.7%
17
5.7%
15
5.1%
11
3.7%
11
3.7%
10
3.4%
10
3.4%
10
3.4%
N
Improve Cotton Prices
Form cotton marketing groups
Decentralize Buying centers
Provide Soft Loans for Inputs
Reliable markets
Improve Infrastructure/transport means
Removal of Middlemen
Provide credit facilities to farmers
Pay on cash basis
Prompt pay
Form cooperatives
Capacity building on the importance of cotton
Unity among farmers
Have many buyers in the market
Decentralize ginneries
89
Non-beneficiary
N
Percent of
Cases
38
25.3%
12
8.0%
15
10.0%
11
12
7.3%
8.0%
13
15
7
8.7%
10.0%
4.7%
20
11
13.3%
7.3%
Perceived Ways of Improving Farmer Relations to Stakeholders
a) Beneficiary districts
Focus group discussions were conducted to obtain to gauge farmer perceptions on regarding
relations. Farmer perceptions on ways of improving interactions with the extension officers
included that the extension services should be extended to more farm visits and farmers
training should be better promoted. The main perceptions regarding researchers were that
they should develop high yielding cotton varieties and provide good quality seeds to farmers
as well as providing new research findings to farmers and visiting farmers’ farms more
frequently. The main perceptions suggested by respondents for improving interactions
between other cotton farmers were that farmers should form marketing groups, to promote
sharing of skills among themselves and to form cotton common interest groups. The
perceptions on how to improve relations between farmers and cotton buyers according to
respondents were mainly improvement of cotton prices by buyers, provision of gunny bags
and soft loans, to locate buying centres near the farmers, to ensure timely purchase of cotton
and to provide cash on delivery. The suggested perceptions on methods of improving
relations between ginners and farmers included improvement of cotton price by ginners,
provision of input loans, timely and suitable cotton seed provision and decentralization of
cotton buying centres among others. The perceptions of respondents on methods of
improving interactions between them and CODA included the control of cotton prices and
markets, visiting farmers and promoting linkages with them, provide farm inputs on credit,
provide cotton technical personnel at the grassroots, to open new cotton buying centres and to
protect farmers’ interests in general.
b) Non-beneficiary districts
The perceptions of the farmers on ways of improving interactions with the extension officers
was that the extension services should be made mainly through farm visit; farmer training,
face to face meetings and advice should be promoted. The main perceptions of researchers
were that they should advise farmers appropriately especially on the varieties to plant,
promote farm visits and have demonstration plots on farmers farms as well as developing
high yielding quality seeds. The main perceptions suggested by respondents for improving
interactions between other cotton farmers were that farmers should have meetings to share
cotton farming skills, form common interest groups, visit each other’s farms and form
cooperative societies. The perceptions on how to improve relations between farmers and
cotton buyers according to respondents were mainly improvement of cotton prices by buyers,
timely purchase and payment, provision of credit facilities, promotion of transparency by
buyers, annual meetings for decision making and to decentralize buying centres. The
suggested perceptions on methods of improving relations between ginners and farmers
included provision of input credit; promoting meetings with farmers, timely cotton seed
provision, high quality cotton production, improvement of cotton prices and decentralization
of cotton ginneries among others. The perceptions of respondents on methods of improving
interactions between them and CODA included promotion of linkages with farmers by
organizing field days/workshops and visiting them, the control of cotton prices and markets,
capacity building of farmers on cotton production and to provide loans and farm implements
to farmers.
90
4.0 Conclusions
Cotton production is undertaken by the farming community on relatively small land parcels
compared to the total land owned by the households in all the survey areas. It is labour
intensive, relying mainly on family labour and on low input use with only 23% and 18% of
the respondents in beneficiary and 11% and 18% in non-beneficiary districts applying
inorganic fertilizers and farm yard manure (FYM) respectively. Cotton production and
marketing constraints vary across the districts. The key production constraints included pests
and high costs of pesticides, unreliable rainfall, poor seed quality and inadequate cotton crop
management skills.
Inadequate mechanization was identified as one of the constraints, especially in Tana Delta,
Lamu West, Baringo North, Magarini and Baringo Central districts. Though tractor hire
services were available, it was limiting since the majority of farmers prepare their land during
the same period at onset of the rains. This leads to soil compaction, soil and water loss and
late planting. In Eastern Kenya, majority of the farmers use oxen ploughs for land
preparation. In Baringo, farmers do not use animal draft due to their traditional attachment. In
addition in Eastern and Rift Valley inadequate chemical applicators were major constraint.
Use of animal power in Baringo North and Central could be addressed through education and
training to demystify some of the beliefs.
The average yield of the project area was 869kg/ha as compared to the documented potential
of 2500kg/ha under research conditions. Inadequate information on good production practices
from extension services and private sector was one of the five major constraints in Baringo
North, Kathonzweni, Tana Delta and Makindu districts. This was mainly attributed to the
limited number of extension staff and also extension research linkages in the districts. This
problem was especially critical in Baringo North and Kathonzweni.
91
5.0 References
Baringo Central District Agriculture Office Annual Report. 2010.
Cotton Development Authority (CODA). Annual Report. 2009.
Eyhorn Frank, Saro G. Ratter and Mahesh Ramakrishnan. 2005. Organic Cotton Crop Guide.
A manual for practitioners in the tropics.
Government of Kenya. Ministry of Planning and National Development. 2003. Poverty
Reduction Strategy Paper 2000-2003. Government Press, Nairobi Kenya.
Ikiara M. M. and Ndirangu K.L. 2002.Developing a Revival Strategy for the Kenyan CottonTextile Industry: A Value Chain Approach. Kenya Institute for Public Policy Research
and Analysis (KIPPRA). Nairobi, Kenya.
Kathonzweni District Agriculture Office Annual Report. 2009
Kitui Central District Agriculture Office Annual Report. 2009
Lamu West District Agriculture Office Annual Report. 2009
Magarini District Agriculture Office Annual Report. 2010
Republic of Kenya, (2000). “Interim Poverty Reduction Strategy Paper for the period 20002003”, Government Printer, Nairobi.
Republic of Kenya. 2007. Kenya Agricultural Productivity Project (KAPP). Rural Household
Baseline Survey. Final Report.
Tana Delta District Agriculture Office Annual Report. 2009
Tharaka South District Agriculture Office Annual Report. 2009.
United States Department of Agriculture: http//www.usda.gov/. Accessed 6th October, 2010.
92
Annex 8. Baseline survey report for Mozambique
ICAC
IMPROVING COTTON PRODUCTION EFFICIENCY IN
SMALL-SCALE FARMING SYSTEMS IN EAST AFRICA
(KENYA AND MOZAMBIQUE) THROUGH BETTER
VERTICAL INTEGRATION OF THE SUPPLY CHAIN
(CFC/ICAC/37)
BASELINE SURVEY FOR LALAUA, RIBAUE AND MURUPULA
IN NAMPULA PROVINCE, MOZAMBIQUE
December, 2012
93
Executive summary
A baseline survey was conducted as part of the activities aimed at improving cotton
productivity in Mozambique. The objectives of the survey were to assess the existing
agricultural practices, production patterns and post-harvest handling. In addition, the survey
documented the needs of the cotton growers in the area of study, identified constraints and
suggested solutions for the identified constraints. The survey was conducted in Lalaua,
Ribaue and Murupula Districts in Nampula Province of Mozambique. Information for the
survey was obtained from the cotton stakeholders including farmers and experts in cotton
production, processing and marketing.
The survey revealed that the area under cotton production and productivity of cotton are low
and vary in the different districts, which suggests that there exists potential for increasing
cotton productivity. The cotton production practices are based on pure stand cotton
production and the cotton growers have limited technical know-how in cotton production
coupled with limited access to the factors of production. Facilitating farmer access to the
factors of production is a crucial endeavour coupled with the necessary capacity building
efforts. Technical skills on post-harvest handling of cotton are also required especially
sorting, grading and packaging. Additionally, improved storage infrastructures are required.
Transport facilities to selling points through company collections of the seed cotton and/ or
hired group transport are considered useful. Improvements in cotton and in particular
adoption of improved cotton production practices will require use of participatory
approaches. Pesticides are widely used in the control of cotton pests in all the cotton growing
areas. There is need for improvement in the marketing of cotton, transportation and
promptness in cotton payments. It is important to introduce integrated farming practices and
facilitate the process of adoption by the cotton growers and by the companies.
The key farmer needs relate to technical know-how and access to inputs and information for
the entire cotton value chain. Quality of the inputs made available also needs to be guaranteed
by the relevant stakeholders. Farmers reported that they needed high yielding cotton varieties
that are less susceptible to pest and disease infestation. Such varieties are likely to generate
higher yields and hence more cotton income. Crop protection equipment especially sprayers
were in short supply and it was thought that the way around this would be pooling resources
to purchase as a group and using them on communal basis under controlled and agreed upon
procedures. Timely supply of inputs was suggested as a measure that would lead to improved
cotton production and productivity taking into account the climatic conditions.
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1.0 Introduction
Cotton production and marketing in both Kenya and Mozambique has been fraught with a
number of problems. Production and marketing approaches are different in both countries.
While in Kenya there is a free market system, in Mozambique there is concession system.
Under the concession system, the Mozambican State represented by the Government through
a contract, entrust cotton companies a given area during 7 years to promote cotton production
by supplying inputs to farmers and to provide extension services. Following the services
offered by the companies the government has allowed the companies to purchase exclusively
all the cotton produced by the farmers in areas under their jurisdiction. No other company is
allowed to purchase cotton from areas under other companies’ jurisdiction. CABI is
executing a project whose key purpose is to improve cotton production efficiency through
formulation and promotion of integrated crop management (ICM) options in cotton
production systems in Kenya and Mozambique by involving private enterprises and public
organizations. The initial approach to achieving this purpose is to conduct a situation analysis
and needs assessment. The results of the assessment would provide indications of the
situation; provide suggestions for improvements and a benchmark for checking
achievements. This requires that relevant and adequate data is collected correctly from all the
project sites, using properly qualified personnel. This report relates to Mozambique.
The project sites in Mozambique are in Nampula Province (Appendix 1). In this province
cotton is produced under specific agreements with cotton companies. The companies provide,
on credit, inputs such as seeds and pest control products, money for the production practices,
and also purchase the cotton produced. Farmers recognize that the company will purchase the
cotton produced. The repayment for the inputs and money/credit provided is from the sales of
cotton. Baseline surveys were conducted in these areas to obtain information that would
describe the production systems of the participating farmers, their yields, use of inputs, costs
and constraints, and what farmers feel needs to be improved within these systems, initial
farmer perceptions of ICM technologies, their socio-economic situation and resource
endowment.
1.1 Objectives
1. Assess existing agricultural practices, production patterns, post-harvest handling
The intention is to assess the methods used in production, area under cotton in the
various districts, cotton varieties, characteristics of the cotton growers, access to the
factors of production, processing of cotton and the marketing practices.
2. Establish pre-adoption socio-economic situation
The situation before the intervention relates to the production practices and the extent
of use of the various production practices, cotton yield and gender differences in the
participation in the production practices.
3. Document needs and constraints of cotton production and marketing
Capacity and development requirements of the cotton growers, constraints in cotton
production and marketing practices will be identified.
4. Suggest solutions for addressing the identified constraints
Identify and document the opportunities that exist to address the constraints in cotton
production, and approaches for the most effective use of the identified constraints.
95
2.0 Methodology
This section provides a description of the study area, the sampling technique adopted, the
method of survey, the nature and sources of data and the various tools and techniques
employed in analysing the data and in evaluating the problems.
2.1. Description of the study area
The project is being implemented in Nampula Province in Mozambique. Two cotton
companies are involved in the project activities and therefore cooperating with the project
team. The two companies involved in the cotton project are SANAM and OLAM. The
baseline report in this case relates to districts under the jurisdiction of OLAM Cotton
Company. OLAM provides inputs to the cotton farmers on the understanding that all the seed
cotton produced would be sold to the same cotton company which would then be able to
recoup the costs incurred. The assistance provided to the farmers is seeds, pest control
products, cash for production practices and technical advice. Two districts (Ribaue and
Lalaua) were involved in the project activities. The selection of these two districts was based
on high cotton production, which is also of strategic importance to the company and farmers
involved in production. A single comparison district (Murupula) was selected to enable
checking the effects of the project on a “before and after”, and “with and without”
assessment.
2.2. Sampling design
Purposive and multistage random sampling procedures were adopted for the selection of the
cotton growers. In the initial stage Nampula Province was purposively selected for the project
activities. In the second stage two districts were selected based on the country policy criteria
indicated. The districts selected were Lalaua and Ribaue. A single district, Murupula, was
also selected for comparison purposes. In the final stage a random sample of 50 cotton
growers was selected from each of the districts. The selection of the cotton growers was
based on the lists of the cotton growers obtained from the company through the company
extension officer in liaison with the IAM agronomist in Nampula. Thus a total of 150 farmers
were sampled from the province for the study.
2.3. Nature and sources of data
Data for the set objectives from the selected respondents were collected using structured and
pre-tested questionnaires and checklists (Appendices 2, 3 and 4). Cotton growers were
personally interviewed to ensure accuracy and comprehension. Data was collected on a large
number of variables, which included age, education, labour, land under cotton cultivation,
resource endowment, crops grown, varieties grown, cotton marketing, constraints in cotton
production and marketing. Data was collected for the agricultural year 2011/12.
Fifty farmers were interviewed from each of the districts participating in the project and the
single comparison district from OLAM Cotton Company. Three focus group discussions
were conducted, that is one for each district including the comparison district. Data was also
collected from key informants who included the agriculture extension officers under the
cotton company that were responsible for activities in the study districts. The agronomists
under IAM in Nampula also provided information for the study.
96
The surveys were conducted at three levels. At the first level individual farmer interviews
were conducted using a questionnaire (Appendix 2). Individual farmer interviews were
conducted to obtain data on gender, resource endowments and cotton yields. These were
followed by focus group discussions to complement information collected from individual
interviews. The focus group discussions were also meant to elicit farmer interactions in terms
of information flow, perceptions of ICM and means of improving ICM. Focus group
discussions were conducted using a checklist (Appendix 3). Focus group discussions were
conducted to corroborate information obtained from the individual interviews and also obtain
additional information as appropriate. The focus group discussions were conducted with two
people; one person asked the questions and the second person wrote the notes that were the
answers/ responses by the participants. The focus group discussions involved aggregating
persons in one place and proceeding with discussions as appropriate. Key informant
interviews were also conducted using a questionnaire (Appendix 4) to obtain specialist data
and information.
2.4. Analytical techniques
The data collected was analysed using descriptive and inferential statistics. Descriptive
statistics used included arithmetic means, percentages and frequencies. Comparison of the
means was conducted using the Chi-Square tests. Other tests used include the F statistics.
Estimates were worked out on per ha. basis and necessary comparisons, interpretations and
inferences executed. District and household level analysis was conducted for all the
categories of data from the different sources. The results from the surveys were presented in
tables and charts as appropriate.
3.0 Results and discussion
3.1 Socio-economic characteristics of the cotton growers
The characteristics assessed among the farmers include age, family size, and education, type
of house owned, resource endowments and sources of income. The assessment was
conducted on the basis of gender and the districts studied. The average age of the cotton
growers ranged from 35 years to 47 years in the different districts (Table 1).
Table 1: Average ages of the cotton growers in the different districts
Male
Female
Ribaue
39.37
38.07
District
Lalaua
46.92
35.00
Both male & female
39.00
46.67
Gender
Murupula
44.71
35.00
44.32
There are no significant differences (F1, 146=3.31, p=0.07) in the ages of male and female
farmers at the 5% level of significance. On average the female farmers have relatively lower
ages than the male farmers in all the districts that is; 37.5 compared to 44.1. There are
significant differences (F2, 145= 3.96, p=0.02) in the ages of the farmers across the different
districts. The ages reported by the cotton growers indicate that cotton is not undertaken by
very old farmers. The middle age category is involved in cotton production indicating that
97
there are not many other income earning opportunities outside cotton production. Indeed,
cotton was ranked as number one among the income generating activities by 89.7% of the
cotton growers. The reasons for the rank provided by the cotton growers were that cotton is a
stable income source because all the cotton produced is sold (Table 2). Livestock production
was less important as indicated by the rank affixed to it.
Table 2: Major income generating activities and the associated reasons
Source of income
Cotton
Rank
1
Sorghum
2
Maize
3
Goats production
4
Sesame
5
Reason for involvement in the activity
Cotton is considered a stable source of farm
household income and is also relatively resistant
to drought
Sorghum is used as both a subsistence crop and a
commercial crop in the study area. Most of the
sorghum is used for subsistence purposes.
Maize is also used for subsistence and commercial
purposes. Most is consumed at home. However, it
is ranked below sorghum because of relatively
lower resistance to drought.
Goats are sold to generate income and are
considered good because of their capacity to
survive in dry areas. Goat keeping is however
limited in the project area. Money obtained from
the sale of goats is used to help in other farm
activities.
Sesame is also produced but it is not as
widespread as the other activities.
The ranking of the key sources of income demonstrated that cotton production is a key source
of income for the farming community in the study area. Other enterprises to supplement
cotton production are also undertaken by the farming community in the area. Among these
are cultivation of other crops and livestock production Farming in the different forms was
considered the key general occupation of the farm households in the area.
The farmers in the project area were resource poor as indicated by the results from the
farmers that participated in the interviews. None of the interviewed cotton growers had a
tractor, ox-cart, ox-plough or a car. A few of the farmers owned radios and bicycles which
were ideally the main resources owned by the farming community in the area. Key resources
required for cotton production were distinctively unavailable among the farming community
in the project area. The types of houses owned by the cotton growers were mainly traditional
houses. Since the type of house owned is a key indicator of the wealth status it may be
inferred that the famers in the project area are less resource endowed. This inference is
consistent with the findings from assessment of the resource base of the farming community
in the project districts.
The majority of the cotton growers (69.3%) had primary level of education. The others had
secondary level of education (3.3%) and no formal education (27.4%). Of those with primary
level of education, the bigger proportion was women who constituted 72.7. Those with
secondary level of education were only men. None of the women involved in cotton
production had secondary level of education (Figure 1). Thus efforts aimed at improving
98
cotton production should involve the key beneficiaries in a participatory manner. The farmers
who are the key beneficiaries should be involved starting from inception of the project
activities. The few educated farmers need to be trained to assure local ownership of the
initiatives for improving cotton production. Demonstrations and field days are important in
this regard. An easier break through would be through farmer field schools where farmers
learn by doing and benefit from each other. Along these lines project efforts using the farmer
field school approach are crucial.
80.0
Percent of each gender
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Non formal
Primary
Male
Female
Secondary
Both male & female
Figure 1: Levels of education of the cotton growers according to gender
The average size of land owned by the farmers varies among the districts and gender. Female
farmers have smaller land parcels (Table 3). However, there are no statistically significant
differences in sizes of land owned by the cotton growers in different districts (p>0.05).
Similarly, there are no statistically significant differences (p>0.05) in size of land owned by
male and female farmers.
Table 3: Average land per household in various districts (Ha)
District
Ribaue
Lalaua
Murupula
(Comparison)
All districts
Gender
Male
Female
Mean
Std. Deviation Minimum
Maximum
3.43
2.17
1.00
10.00
3.47
1.75
1.00
10.00
4.07
3.66
Mean
2.36
1.00
14.00
2.12
1.18
14.00
Std. Deviation Minimum
Maximum
3.65
2.09
1.00
14.00
3.74
2.34
2.00
10.00
Family sizes in the districts vary as well as among the male and female farmers. There are
significant differences in family sizes (p<0.01) between the different districts (Table 4).
Lalaua has the largest family size of 9 persons per household while Ribaue has the smallest
family size of 6 persons per household. Similarly there are significant differences in family
99
sizes (p=0.004) between female cotton growers and male cotton growers. The male headed
families have relatively larger families compared to the female headed households
Table 4: Family size of households involved in cotton production
District
Ribaue
Lalaua
Murupula
(Comparison)
All districts
Mean
Std. Deviation Minimum
Maximum
6.08
1.86
3
12
8.93
2.46
3
21
6.74
7.02
1.86
2.23
3
3
13
14
3.2 Cotton production and post-harvest handling
In the whole of Mozambique, cotton production is based on a zoning (concession) system.
OLAM Cotton Company provides inputs and technical support to the cotton growers in the
three districts involved in the study. OLAM supplies cotton seed and other inputs on credit,
technical extension service, and procures all the cotton produced from the designated area.
This is a legal obligation for OLAM Cotton Company because it is a signatory to the
concession contracts. Farmers receive guaranteed seeds free of charge. In the event that the
seeds are coated with systemic insecticides against early season pests then the cotton growers
are asked to pay MT. 2.0 per kg of cotton seed. In a few cases it was reported that the
company produces cotton seed under contractual arrangements. Under the farmer-company
seed production system the company selects an area where multiply the seeds.
Cotton is mainly produced as pure stand or monoculture by 89.3% of the farmers although a
few farmers practice mixed cropping (Fig. 2). In the event that cotton is produced under
mixed cropping the preferred crop for mixing is maize. Other farmers mix with beans. The
crop used in mixed cropping in principle depends on the farmer. In general any of the crops;
sesame, beans and maize may be used. Shift cultivation was noted as one of the most
common cultivation practice. Weeding, spraying chemicals to control pests, harvesting and
transporting cotton to the aggregation points, selling points or the ginneries was also
undertaken as appropriate. Inputs used in cotton production are supplied by the ginneries.
The seeds used in cotton production are supplied by the cotton companies as credit in kind
when coated, thus farmers are only paying for the chemicals. The understanding is that the
costs involved would be recouped from cotton income obtained after the sale of cotton to the
same companies. Money required for labour used in cotton production is in certain cases
provided by the companies as credit. This is repaid after the sale of cotton to the companies
that provided the credit.
100
100.00
90.00
80.00
Percent involved
70.00
60.00
50.00
40.00
30.00
20.00
10.00
0.00
Male
Female
Pure stand
Both male & female
Mixed cropping
Figure 2: Systems of cotton production
Cotton production practices involve the use of hand hoes mainly. Some farmers use tractors
mainly with the support of the cotton companies. Cotton is grown mainly as a mono crop by
the farmers under the guidance of the cotton companies. The cotton varieties grown were
Albar SZ9313 and CA324. Farmers indicated the need to try other cotton varieties but they
do not know any new varieties that they would try. They would like to experiment other new
varieties. Planting of cotton is undertaken using the seeds provided by the companies in lines.
Hand weeding is undertaken. Spraying is undertaken for the control of pests and diseases.
The crop protection chemicals are provided by the cotton companies.
The cotton farmers set aside relatively small land parcels for cotton production compared to
the total arable land available for crop production activities (Fig. 3). A paired sample t-test
revealed that there are significant differences (p<0.05) between land owned and land under
cotton production. The mean land owned for the entire region is 3.66 ha. while that under
cotton is 2.08 ha. This may be because the cotton growers are also involved in other
enterprises including the production of other crops. There are also significant differences
between the land owned and the land under cotton for the different districts. This means that
while farmers appreciate the importance of cotton as a source of income there are other
factors that contribute to the farmers’ decision to devote smaller land parcels to cotton
compared to the actual arable area available. These factors may be the constraints in input
acquisition and cost, labour, means of production and technology, limited extension
assistance and price among others. In order to increase land under cotton production it is
important that support is provided for labour and other inputs together with technical knowhow.
101
4.5
4
Land size (Ha.)
3.5
3
2.5
2
1.5
1
0.5
0
Lalaua
Ribaue
Murupula
Land owned
All districts
Land under cotton
Figure 3: Land owned and land under cotton production in the various districts
There are differences in production of cotton in the different districts and among the male and
female farmers. Male farmers reported relatively higher outputs compared to female farmers
(Table 5). There are clear and significant differences (p<0.05) in cotton production in the
different districts meaning there exists potential to increase cotton production in areas where
there is low production. Female farmers have relatively lower cotton productivity. The initial
approach would be to target the low cotton producing districts and in each of these districts
put emphasis on women farmers.
Table 5: Cotton production in different districts and gender (kg/ha.)
District
Mean
Lalaua
Ribaue
Murupula
(Comparison)
All districts
Gender
Mean
Male
Female
Std. dev.
510.79
432.22
Minimum
Maximum
343.25
30.00
1200.00
320.43
25.00
1680.00
411.90
451..57
266.05
311.12
Std. Dev.
512.07
275.22
90.00
900.00
25.00
1680.00
Minimum
Maximum
312.77
30.00
1680
207.60
25.00
900.00
Cotton production experience in terms of years under cotton production varied across the
districts but was long in most instances. This indicates that the cotton growers have been
involved in cotton production for relatively long periods. This underscores the importance of
cotton as a source of income although in practice little income is received from cotton by the
farmers. The cotton production experience was reported as a ranging from 11 to 16 years.
Once cotton is mature it is harvested manually. The harvesting team usually carry a small bag
or cloth wrapped on them in which cotton is dropped. The full bags or cloths are emptied at
an aggregation point on the farms. The seed cotton is later removed from the aggregation
points to an area where other post-harvest handling activities are undertaken.
As harvesting continues cotton is put on mats or papers. After harvesting cotton is sorted and
graded. The cotton growers reported limited technical know-how on proper harvesting,
102
sorting and grading of cotton. The cotton was placed in bags weighing between 30kg and
35kg after sorting and grading. The seed cotton bags are usually collected by OLAM Cotton
Company that supplied the inputs to the cotton growers in the area.
A number of problems are associated with inputs’ supply in cotton production. There was late
availability of pesticides and seeds. Limited funds were provided for labour and other
requirements. There was also limited availability of sprayers and other implements. In the
case of pesticides, there is a lack of honesty in buying them by the concessionaire, in regard
to quality. Similarly, on credit repayments, the direct deduction of credit incurred by
producers for seed cotton production during the marketing process is unclear/ not transparent
in the farmers’ view. All agro-inputs for seed cotton production should be delivered directly
to each producers/farmer. Alternatively, the concessionaire should use a transparent/ honest
/trustful intermediary either SDAE or other organization related to agriculture production
process. The seed cotton production system should introduce supplements to enhance soil
fertility, applying for example, chemical fertilizers, even though it is well-known that rains
are erratic in the region. This is necessary given the decline in soil fertility. This might mean
an increase in input costs, but it is expected that the associated productivity would cover the
extra costs. Alternative approaches such as conservation farming may also be tried.
The farmers interviewed reported that they had problems in accessing the inputs. Whereas it
is the case that credit for cotton production practices is given by OLAM Cotton Company the
cotton growers reported having limited access to the credit facilities. Use of improved inputs
such as fertilizers occurred to a limited extent. Farmers indicated that they had limited
information on the appropriate technical skills as well as information on marketing. The main
source of information and the skills were the cotton companies but the farmers thought that
there was lack of transparency in the information provided. This may suggest a need for the
cotton company to organize regular meetings with the cotton growers to update them on
actions taken and how the company intends to improve cotton production and hence the
farmers’ incomes.
Most of the inputs used in cotton production were from OLAM Cotton Company. The
company provided seeds, and crop protection chemicals, especially pesticides. The company
also provided credit to be used for the production practices including the hire of labour where
necessary. The inputs used for the production practices were restricted to what was supplied
by the cotton companies except in the very rare cases where the cotton growers purchased
their own inputs. The farmers reported that the company sometimes provided the inputs
required for crop production late. This in the farmers’ view reduced the efficiency with which
they expected to undertake the production practices and by implication a reduction in the
associated cotton incomes due to low cotton yields.
Farmers in the focus group discussions reported that there were instances where they diverted
the inputs provided by the cotton companies to other crops. Pesticides were the inputs that
were diverted to other crops to the greatest extent as indicated by the cotton growers in the
focus group discussions. There were no clear differences in the levels of input diversion
between the male and female farmers. All the cotton growers reported that whenever they
diverted more pesticides to other crops the seed cotton yield decreased. This indicates that
there was an inverse relationship between cotton yield and the amount of pesticides diverted
to other crops. The level of diversion of inputs calls for measures to facilitate the supply of
inputs especially pesticides for the other crop enterprises. In this case efforts aimed at
improving cotton pest and disease control may consider including key food crops.
103
The fact that the farmers divert pesticides to other crops may be an indicator of there being no
pesticides for use in other crops or limited farmer capacity to purchase inputs for use on other
crops. It may also mean that providers of inputs for other crops are not available in the rural
areas. Most of the crops to which pesticides and other inputs are diverted to are food crops
and sesame. Efforts for improving food security can be conducted alongside improvements in
cotton production. Such efforts should initially target districts where highest amounts of
chemicals are diverted to other crops. The level of access to the cotton production inputs as
reported by the cotton growers and the associated short falls call for measures to improve the
cotton grower access to the inputs. Among the measures suggested by the cotton growers are
facilitating more interested input supplies to supply the inputs to the cotton growers,
formation of stable cotton grower groups to purchase inputs for sharing by the group
members under proper supervision (Table 6).
Table 6: Farmer access to cotton production inputs and required improvements
Cotton production
input
Hoe and machetes
Axes
Seed
Accessibility
Required improvement
Good
Good
Fair
Sprayer
(ULV/Batteries)
Poor
Bags
Poor
Pesticides
Poor
Credit for purchase
Credit for purchase
Create an alternative source of
acquisition, Improve the system of
supply, provide quality seed, Overseeing
the supply system Make seeds available
early, say in October
Create an entity that is responsible for
repairing the micro-ULV, Farmers with
large areas should have a sprayer and
those farmers with small areas should
continue to share the sprayer because it is
expensive to buy and sustain. Have early
access, possibly in November.
Availability of good bags at harvest;
Distribute good bags without holes, April
to May
Increase sources of pesticides that sell at
low price, Improve the application
process, sources of pesticides should be
close to producer, Delivering the
pesticides after confirming
that the
farmer is already undertaking cotton
production
The pest and disease situation on the cotton farms was variable. The level of pest infestation
was relatively higher than the disease incidence on the cotton farms. As a consequence fewer
efforts targeted the control of cotton diseases. Major efforts targeted the control of pests in
the cotton growing area. Among the key pests reported were the sucking insects namely
jassids, aphids, and bollworms and fibre stainer. The main method used in pest control was
the application of pesticides (Table 7). However, a number of problems were associated with
pests. There is limited supply of pesticides, lack of complementary equipment, and pest
104
resistance to the pesticides provided by the companies. This means low efficacy of the
pesticides. It may also mean that the companies supply poor quality pesticides.
Table 7: Pest control methods used by the farmers
Pest control method
Chemical
Advantage
Effective in pests control,
immediate/ fast action
Cultural and botanical extracts
Sustainable, not toxic, does
not pollute the environment
Tolerant Varieties
Less costly
Disadvantage
Pollutes the environment and
toxic to the producers and others,
easily washed off by rain, farmers
have limited skills for spraying
Slow action, low efficiency, does
not control all the pests and
diseases
Not readily available
The expenditures on the pesticides were significantly different between the districts (p=0.03).
The highest expenditure on pesticides was reported in Lalaua District (Table 8).There was a
close association between expenditure on pesticides and the corresponding cotton yield. In
most of the districts there was a positive correlation between expenditure on pesticides and
the cotton yield. This may mean that the pesticides help effectively in the control of the pests
and hence lead to increases in the corresponding cotton. The use of pesticides for pest control
however requires to be executed in a rational manner and in association with other crop
protection practices given the costs involved in the purchase of the pesticides either directly if
available or through credit from the OLAM Cotton Company.
Table 8: Expenditures on pesticides in the different districts (Mt/ha.)
District
Mean
Lalaua
Murrupula
Ribaue
All
Districts
511.38
362.24
545.79
472.37
Std.
Deviation
478.35
239.57
328.25
367.99
Minimum Maximum N
53
71
106
53
2948
1275
1500
2948
48
49
48
145
3.3 Cotton marketing in the project areas
The seed cotton produced was purchased by OLAM Cotton Company, which was the cotton
company mandated by the government to facilitate cotton production in the area and purchase
the seed cotton produced by the farmers in the area. The OLAM Cotton Company supplied
seeds and other inputs, as well as technical know-how to the cotton growers in the area. The
inputs in the farmers’ view were not supplied in adequate quantities and to the expectation of
the cotton growers. The amount of income received by the cotton growers depended on the
quality and quantity of cotton produced. Cotton in the area was graded into grade 1 and grade
2. OLAM Cotton Company purchased the seed cotton and paid the cotton growers after
deducting the costs incurred on behalf of the farmers. Whereas the cotton prices were fixed
after computation of the costs of cotton production including a mark-up for the profit
component, the cotton growers felt that they were not making as much money as they would
have wished to.
105
Net household cotton incomes are relatively low and vary across the different districts (Table
9). There are significant differences in household cotton incomes in the various districts
(p=0.01). Murupula had the lowest household cotton income while Lalau had the highest net
income. The differences in incomes point to the fact that it is possible to increase incomes of
the cotton growers in the districts with lower net incomes given that all the districts belong to
the same agro-ecological zone and are served by the same cotton company.
Table 9: Average household Net cotton income in the project area (Mt/ha.)
District
Lalaua
Gender
Male
Female
Both male
& female
Murrupula Male
Female
Both male
& female
Ribaue
Male
Female
Both male
& female
All
Male
Districts
Female
Both male
& female
Mean
5639.75
1062.50
Std.
Deviation Minimum Maximum
3817.27
125.00 12562.50
1062.50
1062.50
5538.03
3834.84
125.00
12562.50
3235.57
3765.63
699.11
304.94
250.00
3550.00
3183.33
3981.25
3500.60
833.18
250.00
3981.25
5428.41
4367.27
2840.66
2665.73
803.33
875.00
10350.00
9062.50
5121.24
2797.99
803.33
10350.00
3992.67
4045.27
3394.57
2501.51
125.00
875.00
12562.50
9062.50
3998.38
3301.30
125.00
12562.50
Note: Family labour costs are not included in the computation
There are also significant differences (p=0.04) in cotton incomes between the male and
female farmers in the different districts. The price of grade 1 seed cotton per kilogramme was
Mts. 15.0 while that of grade 2 seed cotton is Mts. 11.5 per kilogramme (crop season
2010/11). This converts to USD 0.50 and 0.38 respectively (1USD=30Mts), which is still
relatively low compared to prices in the region. To improve the position of cotton growers in
the value chain it is important that cotton production is considered as a business. Thus the
cotton farmers need to be encouraged to undertake cotton production as a business.
To obtain higher and sustainable cotton incomes, it is important to establish factors that
influence cotton income. To understand factors that affect cotton income multiple linear
regression analysis was conducted. The model used is specified below and the regression
results are indicated in Table 10.
5
Y   biXi  5984.80  3241.70 X 1  346.59 X 2  53.79 X 3  6.32 X 4  8.17 X 5
i 1
The regression results indicate that area under cotton, productivity; expenditure on pesticides
and the family size have a significant influence on income received from cotton.
106
Table 10: Results of multiple linear regression
Description of variable
(Constant)
Cotton Area (ha) (X1)
Total family size (X2)
Age of respondent (years) (X3)
Pesticide costs (Mzn.) (X4)
Productivity (kg/ha.) (X5)
R2 =0.54
Coefficients (bi) Std. Error t
Sig.
-5984.797
3787.254 -1.580
.117
3241.703
550.998
5.883
.000
346.586
284.700
1.217
.227
-53.791
59.352
-.906
.367
6.315
2.560
2.467
.015
8.169
2.585
3.160
.002
The results indicate that it is possible to increase cotton income by increasing area under
cotton and hence cotton income. It is therefore important to encourage cotton growers to
increase area under cotton. This is possible given that a very small proportion of land owned
is put under cotton. Accompanying increase in area under cotton should be improvements in
productivity. This can be achieved by good production practices and crop protection. Use of
more pesticides on cotton is associated with higher cotton incomes. This may be an indicator
that the pesticides improve pest management and hence lead to higher cotton outputs. This
finding indicates that to reduce pesticides usage in cotton production adequate monitoring
and early control will be necessary to reduce quantities of pesticides to be used. There is a
positive association between family size and income from cotton. This may be because large
families provide family labour especially where costs to hire labour could be prohibitive.
3.4 Farmer perceptions about integrated crop management
The cotton growers that were interviewed reported that integrated crop management where
many crops and practices are used would be good to allow for diversification in the
production practices and the crops to be grown. The use of crops such as maize and soya
beans was considered and the farmers felt that it would be good for the integrated pest
management practices to be supported with the necessary technical know-how from the
agricultural extension officers. The required information, skills and tools need to be provided
to the cotton growers. To facilitate effective uptake of the integrated crop management
practices more training to the facilitators was considered necessary. The OLAM Cotton
Company extension team may require further training in integrated crop management and
other good agricultural practices given that they have been involved in the promotion of
cotton alone with less diversified production approaches. A proper review of the credit
requirements of the cotton growers needs to be considered to ensure that adequate amounts
are provided to facilitate efficient and effective cotton production. The need for the stated
support is attributed to the restricted use of inputs such as fertilizers that are associated with
improved crop yield. The use of pesticides from the cotton company alone may generate
dependency in the farming community. Alternative sources of inputs to be used in cotton
production needs to be considered. This suggests opening up input supply system to other
interested participants in the area.
The cotton growers that were interviewed did not demonstrate good knowledge of integration
of good farming practices. Only a few cotton producers (13.3%) practice mixed cropping.
Discussions with farmers revealed that there is a belief that mixing crops may not lead to
good crop yields and monoculture is practiced for as long as six years. The producers practice
107
monoculture because that is the recommendation given by companies. The company needs to
introduce integrated farming practices and facilitate the cotton growers in their quest for
adoption of the new production practices. Along the same line IAM should also source, adapt
and disseminate integrated farming practices. The farmers have insufficient knowledge and
technology information, so there is a need to disseminate such packages. In order to hasten
the adoption process it may be appropriate to use local lead farmers to serve as models to
facilitate adoption of the technology. This approach could be supported by field days,
demonstrations and the farmer field schools.
Farmers do not practice cutting and burning of stalks as per regulation. To address this
weakness it will be good if producers were mobilized to cut and burn and perform rotation.
Integrated crop management would give advantage to the producers in terms of use of
resources. Use of strip intercropping can enable production of cash crops and food crops at
the same time.
3.5 Needs of farmers in cotton production and marketing
There is limited knowledge regarding good agricultural practices and varieties in cotton
production. Farmers require varieties that have higher cotton outputs. Most farmers do not
know the actual variety, which shows that there is lack of information about the appropriate
varieties. A few farmers indicated that they would like a variety with high performance in
terms of income. Among the few varieties CA-324 would be the most popular and preferred
variety. The varieties preferred are those that have high yields and hairy to prevent and
minimize the combined effect of attacks from insects/pests. Pesticides are relatively
expensive and hence in the short run the cotton growers will require support in terms of
subsidized prices or group formation to pool resources for the purchase of pesticides and
other inputs.
In the farmers’ view the varieties that are being used require intensive chemical applications.
The new varieties should be such that they require less care in terms of crop protection and
application of chemicals for a long time. This means that use of pest tolerant varieties would
be preferred by the farmers. There is dissatisfaction with the current cotton varieties because
they are very susceptible to pests attack. Hence new varieties would be preferred. Treated
cotton seeds that are tolerant to pests are needed. The support required by the farmers is
timely provision of cotton inputs in general. There is need for fertilizers and credit for labour
as well as affordable farming machinery for the smallholders.
Technical skills in crop production practices were notably limited among the cotton growers.
Farmers require skills and knowledge in good agricultural practices. The producers want to
learn how to do maintenance of sprayers and have support to distribution of kits for crop
protection. In addition farmers require technical skills on identification of pests, types of
pesticides and how to use the pesticides. Pest management and application of chemicals are
skills required urgently. Training in plant protection is considered necessary. This
information should be disseminated through agricultural extension officers. Knowledge of
handling crop protection processes especially spraying is crucial for pest control. The help
required for the farmers to acquire the skills is practical demonstrations on planting, spraying,
harvesting and mixing of the pesticides. Good conditions for training are required. Materials
for practical demonstrations need to be made available. These materials should be
accompanied with pamphlets, hand outs, brochures and possibly radio programmes on the
husbandry practices.
108
It is important that the seeds of high yielding cotton varieties are readily available.
Availability of seeds should be associated with provision of technical assistance. Tests need
to be performed for identification of appropriate varieties, affordable to farmers and
popularize such varieties. Improved seed varieties can be popularized by cotton companies
and alternative input providers. Additionally, identification of varieties should be followed by
tests of adaptation, multiplication and release of the variety; and practical demonstrations onsite. In case of any new variety, the support required is technical assistance in caring for the
new variety; the variety adaptation trials should be done on time and the seed should be easily
accessible to farmers. The concessionaires system in place and the cotton companies provide
seeds. Improvement in farmer access to new cotton varieties should be guaranteed. This
means that there is need for alternative suppliers of seeds and other inputs. This would
preferably be institutions/ organizations that are not cotton companies. Alternative seed
providers would increase farmer access to the improved variety seeds and encourage
competition which is assumed to increase efficiency in the supply system. CIMSAN/IIAM
and IAM need to be directly involved in overseeing the supply situation in terms of both
quantity and quality. More credit needs to be made available especially for weeding. This
may involve provision of information about the various sources of credit and the terms and
conditions for credit from the selected institutions. Training on sourcing credit and profitable
use is necessary. Transportation of cotton to the ginneries needs to be improved. Skills on
grading and sorting of cotton are required. Consideration for increasing seed cotton prices is
important.
The cotton growers reported that there was a shortage of sprayers, batteries, gloves, masks
and boots that were considered crucial for effective application of crop protection chemicals.
The farmers’ views were that the sprayers should be those which are easily accessible.
Farmers do not use protective equipment while spraying pesticides, which puts their health at
risk.
3.6 Constraints in cotton production and marketing
High costs of pesticides, lack of pesticides, shortage of labour, late arrival of pesticides in the
fields and limited availability of sprayers and accessories were cited as key constraints in
cotton production in the project area. There is a shortage of technicians and lack of technical
know-how among the farmers. Prices of seed cotton are low according to the cotton growers.
This is possibly because only the designated companies purchase the seed cotton in the area.
The companies, which are ideally monopolies, offer only 5% on top of the minimum price.
The price paid for the cotton is not enough to compensate the farmers for the costs of cotton
production especially the labour costs. Low cotton yields are obtained and it was noted that
improved equipment for agricultural production were lacking.
The OLAM Cotton Company was the one mandated to purchase seed cotton in the various
cotton producing locations. This approach is meant to ensure that the company that supplied
inputs to the cotton growers is the same company that would purchase the seed cotton from
them and hence a reduction in default rate of the cotton growers that received credit. It is also
meant to encourage the company to invest maximum efforts in cotton production in the area.
There were some instances of late collection of seed cotton by the company that led to
reduction in quality of cotton as result of poor storage facilities in the cotton growing areas.
109
Some farmers indicated that they thought the weighing scales used were not accurate and
hence led to underweight of the cotton produced by the farmers. The low weights according
to the farmers would translate into low cotton incomes. The farmer perceptions with regard to
weighing of cotton and associated cotton income require to be addressed to establish whether
or not they are correct. These perceptions point to issues relating to lack of adequate market
information and access to markets. In this regard it is important for the cotton growers to be
given adequate market information in terms of weights, deliveries, payments and timing of all
the market related functions.
3.7 Suggestions on how to improve cotton production and marketing
It is important to assure timely supply of the inputs used in cotton production. Access to
inputs on a timely basis can assure improvement in cotton production efficiency and lead to
increased cotton yield. The inputs in this respect include seeds, pesticides and sprayers.
Provision of finance for cotton production practices is crucial. There is need to increase
and/or create conditions for use of improved technology in cotton production.
In order to improve cotton production it is necessary to provide food stuffs and physical
capital to the cotton growers. A strong agreement between IAM and the dealers (cotton
concessionaire companies) is warranted. Cotton varieties which are drought resistant need to
be introduced. Appropriate and affordable mechanization is the best way to increase and
improve cotton production. An improvement in interaction between the company and
producers; creating credit facilities for farmers, and soil improvement through fertilizer
application, mechanization of cotton production and an increase in area under cotton can
improve overall cotton production.
It is necessary to facilitate farmer access to credit facilities for all the cotton production
requirements to avoid limited involvement in some production practices that would
eventually lead to low cotton yield and the corresponding cotton income. The company
extension staff that deal with the cotton growers need to apportion more time for interaction
with the farmers to disseminate the necessary skills and information to the cotton growers.
Post-harvest handling of cotton was noted to have issues just as production and hence call for
capacity building at the cotton grower level. In this case skills in sorting, grading, packing
and storage are necessary.
The contact between extension technician and farmer is limited to input provision and not
knowledge transfers. It is also necessary to improve the process of weighing and grading of
seed cotton. Farmers need to be mobilized to constantly grow the cotton; the cotton
production system should include also food crops; mechanization of cotton production;
increasing the cotton crop area; mobilize producers to plant early; have a history/record area
of producers; strengthen the communication and complement ability between institutions.
The timing of the cotton production practices need to be explicit to the cotton growers and at
the same time facilities provided to encourage undertaking of the activities. It is necessary to
create a business club/awareness to avoid wasting the costly harvest of seed cotton. Use a
mechanism of sorting and grading cotton in which the cotton does not go to waste. It is
necessary to provide tractor or animal traction in potential areas.
To improve cotton marketing it is necessary to weigh the cotton with precision and
transparency to avoid suspicion; clearly defining and explaining to the producers the criteria
to grade seed cotton quality and create good conditions to transport seed cotton to the
110
company for processing. There is need for improvement of transport from the farmers’ field
to the company. Finance and/or credit should be supplied in time to the cotton growers and
payments to the cotton growers need to be timely. It is necessary to encourage
associations/farmers organization to conduct marketing of cotton to the companies on behalf
of the farmers. To empower the said association it is important that payments are made for
the services they provide to the companies.
3.8 Policy and regulatory issues on production and marketing
Cotton production in Mozambique is conducted under the concession system, in which a
ginning company is licensed to operate in a given area and smallholders are obliged to sell to
the cotton company operating in their area. This is meant to protect the ginning company
from competition for seed cotton as they are the sole provider of associated inputs on a credit
basis to farmers. This system does not allow side-selling and is expected to encourage the
cotton companies to invest in provision of inputs, credit and technical support.
The cotton growers had a feeling that the Cotton Company does not provide adequate
technical support to the cotton growers. Whereas it is the case that prices are set after
considering all the production costs; the cotton growers felt that income received was not
adequate given the production and processing activities that they undertake at the farm level.
The regulations for enforcing the quality standard were not clear to the cotton growers. This
indicates a need for information to be adequately delivered to the cotton growers regarding
measures to assure cotton quality and the associated benefits and losses. In this case standard
production and processing practices need to be known to the cotton growers as well as other
post-harvest handling procedures such as sorting, grading and storage pending collection by
the cotton company. The policy environment may benefit also from suggestions for
improvement (Table 11).
Table 11 Policy issues and suggested improvements
Practices
Cotton production
Post-harvest
handling
Marketing
Environment
Policy and regulatory issues
Regular review of the concession system
with regard to efficiency in service
delivery. Supervising the distribution and
use of seed, pesticides and other inputs to
maintain quality. Ensuring cotton grower
access to the necessary technical know-how
The cotton company needs to indicate to the
cotton growers the types of post-harvest
handling procedures that need to be
undertaken and the necessary timing. Verify
that producers are doing the cutting and
burning.
Surveillance of the weighing process,
overseeing the sorting, grading and
packaging processes.
Remarks
The producers need to be
allowed to sell seed cotton
on a competitive basis.
This may involve other
buyers given the assurance
of repayment of credit
Prevent the use of seed of
last campaign. Farmers
should be encouraged to
use seed of the current
season.
Companies
monitored
government
maximum
farmers
Require producers to properly burn or bury Identify
111
to
be
by
the
to assure
benefits to
suitable
Practices
Labour regulation
Policy and regulatory issues
Remarks
the container of pesticides and used authorities
to
batteries; wash sprayers in provided areas. spraying process
There is need for a unit to collect empty
pesticide containers for disposal
Impose discipline during the spraying and
after this operation, provide protection for
the farmers
handle
4.0 Conclusions
Land under cotton is relatively small compared to land owned. Hence, there exists potential
for increasing area under cotton in the all the districts. Similarly, women farmers own smaller
land parcels and devote a relatively small area to cotton production. Most cotton growers
have low levels of education. Accordingly, special methods should be used when efforts are
undertaken to improve productivity.
Key constraints at the production level include low quality seed, pests and high cost of
pesticides, inadequate knowledge of good cotton production practices, inadequate access to
inputs and unreliable rainfall. Late availability and limited quantities of inputs necessitate
alternative systems for the supply of inputs or improvement in delivery by the cotton
company. Management of pests and diseases depends mainly on pesticides. Hence diversity
in terms of control methods is worth consideration. Integrated crop management would be a
good complementary approach. There are limited crop production technical skills among the
cotton growers hence a need for the requisite support. The cotton company needs to invest
more in the provision of the necessary technical know-how to their staff to disseminate to the
cotton growers. Training and capacity building are required to address shortage of technical
skills. A coordinated approach involving all the cotton stakeholders may be necessary to
ensure provision of the necessary services to the cotton growers.
Seed cotton production and productivity is relatively low in all the districts and there are
significant differences. There exists potential for increasing cotton production, productivity,
marketing and incomes. Efforts to increase production and productivity need to be
undertaken urgently, especially targeting the districts with lowest production and
productivity.
There is need to promote improved storage/warehouses as well as allocation of
products/chemicals to enhance the conservation of seed cotton. There are no special
arrangements for post-harvest handling. There is need to mobilize farmers to build improved
storage /warehouse for seed cotton. Floors with roofs need to be constructed and technical
assistance provided during cutting and burning. Information on good agricultural practices
needs to be effectively disseminated to the cotton growers in all the districts. Marketing
activities need to be undertaken in a manner that can assure efficiency in all the activities and
hence increased income to the cotton growers.
112
5.0 Recommendations
The recommendations arising from the results of the survey are as follow:
 Capacity building is required for the cotton growers in all the three districts. This is meant
to provide the necessary technical know-how to the farmers in terms of good
agricultural practices that can assure improved cotton productivity. The technical knowhow provided should cover the entire cotton value chain. It will be necessary to provide
support together with information to change perceptions regarding the pure stand and
mixed cropping alongside the integrated crop management practices.
 Access to the inputs required for crop production needs improvement in terms of
timeliness, quantity and quality. In this regard some system needs to be put in place to
assure the quality standards are maintained. Thus a coordinated approach involving all
the stakeholders with IAM as the lead is called for. The government through the
relevant institutions need to also participate in the supply of inputs. An alternative
system for input provision that will allow farmers to decide where to acquire inputs
should be tested.
 Good efforts need to be undertaken to make available more high yielding varieties with
pest and disease resistance. The priority should be on pests since diseases are not a
major constraint. This should be complemented with a wide range of methods for pest
and disease control
 Training on post-harvest handling of cotton is required. This should be associated with
provision of appropriate storage and packaging facilities. Improving access to market
information through the delivery formats advocated for.
 The cotton growers in the project districts need to be facilitated to adopt the integrated
crop management practices. OLAM Cotton Company and other stakeholders need to
help the cotton growers given the perception that only pure stand cotton would do best
in the area and the limited access to other technologies for cotton production in the area.
This action will also require a coordinated approach by the other stakeholders to fast
track. The integrated crop management practices need to be adapted as appropriate
depending on the cotton grower capacity.
113
Acknowledgments
This baseline survey was undertaken as an activity in the project entitled, “Improving Cotton
Production Efficiency in Small-Scale Farming Systems in East Africa (Kenya and
Mozambique) through better Vertical Integration of the Supply Chain (CFC/ICAC/37)”. The
project is jointly funded by the Common Fund for Commodities (CFC) and the European
Union (through its All ACP Agricultural Commodities Programme - AAACP) with in-kind
contribution from the governments of Kenya and Mozambique, and CABI. The project has
been developed in close consultation with the International Cotton Advisory Committee, the
project’s Su17pervisory Body, as per CFC’s policies.
114
Appendices
Appendix 1: Project areas in Mozambique
115
Appendix 2: Individual/ household survey questionnaire
I.1.
Section A: Identification
District: ………..……….. Administrative Post ………………………..……Date …..…...…
Locality………….Village/Regulado ……………Area of Influence/Agency ……………
Name of enumerator: …………………………………………………….…………………
Name of respondent: ……………….……………..……….……...……………………….…
Relationship of respondent with household head (circle answer): head=1, spouse=2, son=3,
daughter=4, other specify=5 ……………………………………………….
Section B: Household and socio-economic characteristics
1. Age of household head/respondent: ……………..years
2. Gender of household head (circle as appropriate): Male=1, Female=2
3. Highest formal education attained by the respondent (circle answer): non-formal
education=1,
primary=2, secondary=3, University=4, other (specify) =5 ………………
4. Main occupation of the household head /respondent (circle answer): farmer=1, business=2,
teacher=3, government employee=4, NGO employee=5, other (specify) =6 -----------------5. Household size: adult male ------- adult female --------- children (under 18 yrs)--------------6. Type of house owned (tick answer): 1=permanent, 2= semi-permanent, 3=traditional:
7. Asset ownership (number): cows: ------goats: ------------------- sheep: ------------- donkey: ---oxen: --------- bicycle: ------------motorcycle:------------car: -----------wheel burrows--oxen cart:--------------- donkey cart:--------oxen plough:-------- tract-------------Radio
others (specify) ---------------------------------------------------------------------------------------8. Total size of land owned by the household (ha) ------------------------------------------------9. Type of land ownership (individual, communal, hired, etc.) -------------------------------------10. In the table shown below please list and rank in order of importance five major crops/
enterprises that you were involved in the last crop season you grew cotton, annual income
from each and rank (prioritization of cotton as an income earner)
Annual income (Meticais)
Crop/enterprise
Area (ha)
Ranking
(200…)
Cotton
11. Is there a women cotton association in this area? Yes/ No ------------------------------12. If yes, state the name (s) of the women association ---------------------------------------------13. Are you a member of any farmers’ group/association? Yes/No --------------------------14. Please state the name of the association that you belong to -------------------------------Section C: Cotton production
15. Which year did you first plant cotton (cotton farming experience)? ….……………….….
16. Please state your assessment of the timeliness of seed availability: late=1, on time =2
17. In the table shown below please state the variety and system of cotton production
Cotton
System under which Current total Cotton production last
variety
it is grown
area (Ha)
season 200.. (kg)
Total cotton area and annual
production
116
System of production: pure stand=1, Mixed cropping =2
18. Give reasons why you practice the production system mentioned in question17above?
……………………………………………………………………………………
19. If you do mixed cropping, which crop do you mix with? ………………………………….
20. Do you practice crop rotation? Yes = 1; No = 2 …………………..……………………….
21. If your answer to question 20. above is ‘Yes’ explain the reasons for practicing crop
rotation--------------------------------------------------------------------------------------------------22. Indicate who, when and how the following activities are done in cotton production?
Activity
When (Month) Who* How**
Remarks
Land preparation
Planting
First weeding
Second weeding
Third weeding
Spraying chemicals
Harvesting
Transportation
Cotton selling
Decision on cotton area
*Who: 1=Men, 2=Women, 3= Girls (7-18years), 4=Boys (7-18years
**How: 1. Hand 2. Oxen 3. Tractor 4.Others (Specify)………
23. In the table shown below please indicate the types, quantities and costs of the inputs used
in cotton production in the last season/year that you last planted cotton.
Type of input
Quantity
Units ((litres/
Cost
millilitres/ kg/ no )
Seeds treatment
Pesticides:
1..
2.
3.
4.
Labour
24. Please specify type, quantity and source of pesticides used on other crops in the table
below
Type of pesticide
Quantity of
Source of pesticide
pesticide
25*. What problems are associated with input acquisition? ………………………………….
26. Do you have any contractual arrangements with the concessionaire company? Yes=1
No=2
27. If yes Please specify the contractual arrangements that you have for cotton production and
marketing ----------------------------------------------------------------------------------------------28. Please state the benefits obtained from the contractual arrangements --------------------29 Please explain how cotton is handled after harvesting (sorting, grading, etc.) ---------------117
30. Please indicate the constraints you face in cotton production in the table below.
How are you trying /did you try to
Rank
Constraints
overcome the constraint?
R1 R2
(interventions/ control)
Diseases related
Pests related
Jassid (Emposca fascialis)
Aphid (Aphis gossipii Glov.)
American Bollworm (Helicoverpa armigera)
Red Bollworm (Diparopsis castanea Hmps)
Pink Bollworm (Pectinophora gossypiella
Saund)
Fiber Stainer (Dysdercus fasciatus)
Others (Specify)
Inputs & Equipment related
High pesticide costs
High herbicide costs
Lack of pesticides
Shortage of labour
High cost of implements
Late availability/ accessibility of ULV
Other (specify)
Marketing Related
Lack of market information
Lack of or inadequate transportation
Delayed payment
Low prices of seed cotton
Poor or lack of storage
Others (specify)
Note: R1= rank within individual groups, R2= overall rank among all constraints
31* What support services (means) do you require to improve cotton production and
productivity? ------------------------------------------------------------------------------------------32 Where do you obtain credit/ money for cotton production? (Ginner=1, Banks=2, Salary/
wages=3, Business=4, Remittance=5, other (specify) ------------------------------------33. If you obtained credit/ money in the last crop season, please state amount, sources and
purposes
Amount
Source
Purpose
34. What are the problems associated with credit acquisition and repayment? ------------------Section D: Cotton Pest and disease control
118
35. Please state the different methods that you used for the control of diseases and pests in the
last crop season and costs involved.
Method
Costs
36. What problems do/did you encounter in the control of cotton pests and diseases? ---------37. If you do/did not use any control method, give reasons why?
Lack of knowledge=1, It is difficult to apply =2, Lack of labour=3,
Others (specify) ---------------------------------------------------------------------------------------38*. What skills, knowledge and support would you like to acquire to improve the control of
pests and diseases in cotton?-------------------------------------------------------------------------39*. State the help that you require for each of the stated skills. / Knowledge mentioned in
number (38) above. -----------------------------------------------------------------------------------40. Please list any development programme/activity being carried out in your area to
tackle the cotton production, pest and disease constraints -------------------------------------41. Where do you get advice on better cotton farming practices? government extension
officer=1, neighbours=2, NGOs=3, private companies=3, none=4, others (specify) ------42. What type of advice do you get? ------------------------------------------------------------------43*. Please suggest methods for improving cotton production ------------------------------------Section E: Marketing of cotton
44. How do you harvest cotton? (circle answer) in a single phase=1, in more phases=2 -------45. Please state the quantity of cotton sold in the last crop season (2008/09) and the price per
unit
1st Grade cotton ------------- kg/bags Price per kg/bag (delete as appropriate) -------------2nd grade cotton ----------------kg/bags Price per kg/bag (delete as appropriate) ----------46. What is the current farm gate price for cotton? (Please specify unit and price per unit)
Price per kg of 1st grade -------------Price per kg of 2nd grade -------------47. Please specify the type of costs involved in cotton marketing and the actual amounts
e.g. transportation --------------------------------------------------------------------------------48*. Please indicate all the problems you encounter in cotton marketing. poor seed cotton
prices=1, low seed cotton volumes=2, long distance to ginning facility=3, others (specify)
-----------------------------------------------------------------------------------------------------------49*. Please suggest methods for improving cotton marketing ------------------------------------------------------------------------------------------------------------------------------------------------50*. What assistance do you require for cotton marketing? ----------------------------------------51. Please suggest how to improve information flow between yourself and the cotton
company technician (extension officers)
------------------------------------------------------52. Please suggest how to improve information flow between yourself and researchers
53. Please suggest how to improve information flow between yourself and other cotton
farmers… ---------------------------------------------------------------------------------------------54. Please suggest how to improve information flow between yourself and cotton ginneries--55. Please suggest how to improve information flow between yourself and IAM Delegation
-----------------------------------------------------------------------------------------------------56. Please suggest how to improve information flow between yourself and other stakeholders
-----------------------------------------------------------------------------------------------------119
Appendix 3: Focus group discussion checklist for farmers, extensionists & other actors
1. Using a table as the one shown below please indicate five major income generating
activities of farmers
Source of income
Rank
Reason
(1,…,5)
2* State the cotton varieties that you do not grow but would wish to grow-----------------------3* State the support that you require to try new cotton varieties------------------------------------4. Generate a list of major cotton production constraints by consensus and provide a matrix
scoring for the constraints.
5. Using the table format shown below please obtain the rank of accessibility to improved
cotton production inputs, and mechanisms for improving accessibility.
Cotton production
Rank Accessibility Required improvement
input
6. Obtain stakeholder perceptions about the husbandry practices.
7. Discuss the need /consensus about building resilience of cotton to diseases/pests
8. Using the table formats shown below please document the pest and disease control
methods used, starting with the most effective, plus the advantages and disadvantages of
each method as well as percentage of farmers using each method.
Pest control method
Percentage
Advantage
Disadvantage
of farmers using it
Disease control method
Percentage
of farmers using it
Advantage
Disadvantage
9*. Please provide suggestions on how to improve cotton production-----------------------------10. Attitudes and views about trying integrated crop management practices
11. In the table format shown below please indicate the knowledge and skills required in
cotton production. (Sources, access and relevance etc.)
Knowledge/skills Source of
Accessibility of
Relevance of
required
knowledge/skills
knowledge and skills* knowledge and
skills**
* 1 = Easily accessible; 2 = Accessible; 3 =Rarely accessible; 4 = Not accessible
** 1 = Very relevant; 2 = Relevant; 3 = Not relevant
12. What tools and equipment are bottlenecks in cotton production and the control of pests
and diseases? -13*. What skills, knowledge and support would you like to acquire to improve the control of
pests and diseases
14*. State the help that you require for each of the skills. / Knowledge stated in number 13.
15*. Please provide suggestions on how to improve cotton marketing----------------------------16. Using the table format shown below please discuss policy and regulatory issues touching
on: production, post-harvest handling, marketing, environment and labour regulations
Practices
Policy and regulatory
issues
Cotton production
Post-harvest handling
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Remarks
Marketing
Environment
Labour regulation
121
Appendix 4: Key informant checklist for selected stakeholders
Questionnaire number ---------------------------------------------------Date --------------------------Name/ title of the respondent ----------------------------------------------------------------------------Name of organization the respondent belongs to -----------------------------------------------------1* State the cotton varieties that farmers do not grow but would wish to grow------------------2* State the support required by farmers to try new cotton varieties-------------------------------3. List the major cotton production constraints
4. Using the table format shown below rank the farmers’ accessibility to improved cotton
production inputs, and what is required to improve accessibility.
Cotton production
Rank Accessibility Required improvement
input
5. Provide suggestions on how to improve cotton production---------------------------------------6*. What is required to improve post-harvest handling of cotton?
7. State your opinion on the need for building resilience to cotton to diseases/pests
8. Using the table formats shown below please document the pest and disease control
methods used, starting with the most effective, plus the advantages and disadvantages of
each method
Pest control method
Advantage
Disadvantage
Disease control method
Advantage
Disadvantage
9. State your views about trying integrated crop management practices
10. In the table format shown below please indicate the knowledge and skills required in
cotton production.
Knowledge/skills Source of
Accessibility of
Relevance of
required
knowledge/skills
knowledge and skills* knowledge and
skills**
* 1 = Easily accessible; 2 = Accessible; 3 =Rarely accessible; 4 = Not accessible
** 1 = Very relevant; 2 = Relevant; 3 = Not relevant
11. What tools and equipment are bottlenecks in cotton production and the control of pests
and diseases? -12*. What skills, knowledge and support do farmers require to improve the control of pests
and diseases in cotton?
13*. State the help that is required for each of the skills. / knowledge stated above
14*. What factors are likely to limit farmer capacity to take-up any new cotton technology
15*. Provide suggestions on how to improve cotton marketing-------------------------------------16. Using the table format shown below please discuss policy and regulatory issues touching
on: production, post-harvest handling, marketing, environment and labour regulations
Practices
Policy and regulatory
issues
Cotton production
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Remarks
Post-harvest handling
Marketing
Environment
Labour regulation
123
Annex 9. Impact assessment report for Mozambique
ICAC
IMPROVING COTTON PRODUCTION EFFICIENCY IN
SMALL-SCALE FARMING SYSTEMS IN EAST AFRICA
(KENYA AND MOZAMBIQUE) THROUGH BETTER
VERTICAL INTEGRATION OF THE SUPPLY CHAIN
(CFC/ICAC/37)
IMPACT ASSESSMENT OF ICM ADOPTION IN MOZAMBIQUE
DECEMBER 2013
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Acknowledgments
Impact assessment was undertaken as an activity in the project entitled, “Improving Cotton
Production Efficiency in Small-Scale Farming Systems in East Africa (Kenya and
Mozambique) through better Vertical Integration of the Supply Chain (CFC/ICAC/37)”. The
project was jointly funded by the Common Fund for Commodities (CFC) and the European
Union (through its All ACP Agricultural Commodities Programme-AAACP) with in-kind
contribution from the governments of Kenya and Mozambique, and CABI. The project was
developed in close consultation with the International Cotton Advisory Committee, the
project’s Supervisory Body, as per CFC’s policies. We thank CFC for their inputs.
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Executive summary
In Southern and Eastern Africa cotton yields are low mainly due to poor quality planting
seeds, poor and untimely land preparation plus inadequate pest control measures, but there is
wide scope for improvement in production efficiency within the smallholder sector. In 2009 a
project was started in Kenya and Mozambique to improve cotton production efficiency
through formulation and promotion of integrated crop management (ICM) options in cotton
production systems by involving private enterprises and public organizations. The initiation
workshop for the project was in Maputo, Mozambique. The project specifically aimed at the
introduction of best practice ICM packages, promotion and adoption of ICM packages,
building stakeholder linkages for sustaining ICM and evaluation of the impact of ICM
adoption. The ICM strategy was based on a Farmer Participatory Training and Research
approach for adoption by cotton farmers. The project was funded by the Common Fund for
Commodities (CFC) and the European Union (through its All ACP Agricultural Commodities
Programme-AAACP) with in-kind contribution from the governments of Kenya and
Mozambique, and CABI.
In Mozambique, Instituto do Algodão de Moçambique (IAM) and CABI implemented a
project in five districts of Nampula Province to improve production and productivity of
cotton. The project targeted small scale cotton farmers. In Mozambique cotton production
was undertaken under the concession system where different cotton companies were
allocated different areas, by the government, to support cotton production by supplying inputs
and purchasing seed cotton produced in their area of jurisdiction. Thus, Mozambique
enforced a concession system that protected the ginning company from competition for seed
cotton. The key thrust in the project in Mozambique was to promote use of integrated crop
management (ICM) practices and to provide the relevant information for production and
marketing of cotton in a contract system of cotton production. A farmer field school approach
was used in which farmers’ capacity was built in the use of good production practices and
how to access inputs and information. At the end of the project an impact assessment was
conducted to establish the extent to which the initiative contributed to changes in farmer
practices, productivity, cotton income and perceptions about cotton production. The
assessment involved a comparison of adopters of the ICM practices and non FFS farmers in
other non-project (comparison) districts, using a difference-in-differences method.
Results indicated that farmers using ICM practices increased the area under cotton as well as
the productivity of cotton. There were also corresponding changes in the famer perceptions
about cotton, and incomes from cotton were higher for the participating ICM farmers in the
project areas (as compared to non-participating farmers). The project farmers had better
access to information compared to the non-participating farmers in the area and demonstrated
a better knowledge of cotton production practices compared to the non-participating farmers.
There were no significant differences in levels of education among those using the ICM
practices and those using the conventional practices in the area which would indicate that
participatory approaches would be most ideal to increase farmer capacity in cotton
production. Good cotton production practices especially the use of ICM demonstrated
capacity to improve cotton productivity. This is due to the fact that the cotton growers that
adopted the ICM practices realized better seed cotton yields. Sustained increase in
productivity could be achieved by using a coordinated approach that would involve all the
cotton stakeholders especially the cotton companies to improve access to inputs and timely
collection of seed cotton as well as payments. This assertion is based on reports by some
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cotton growers that in some instances the cotton companies delayed to provide the inputs as
well as collecting the seed cotton and making payments. Efforts to improve cotton processing
particularly post-harvest handling, packaging and storage would be necessary to improve on
the quality of the cotton produced. This would translate in to better income for the cotton
growers in the project area and other areas as well.
1.0 Introduction
In Southern and Eastern Africa cotton yields are low mainly due to poor quality planting
seeds, poor and untimely land preparation plus inadequate pest control measures, but there is
wide scope for improvement in production efficiency within the smallholder sector. CFC
made a call through ICAC for project initiatives to address cotton productivity issues. In 2009
a project titled, “Improving cotton production efficiency in small-scale farming systems in
East Africa (Kenya and Mozambique) through better vertical integration of the supply chain”,
was started in Kenya and Mozambique. The purpose of the project was to improve cotton
production efficiency through formulation and promotion of integrated crop management
(ICM) options in cotton production systems by involving private enterprises and public
organizations. The initiation workshop for the project was in Maputo, Mozambique in 2009.
The project specifically aimed at the introduction of best practice ICM packages, promotion
and adoption of ICM packages, building stakeholder linkages for sustaining ICM and
evaluation of the impact of ICM adoption. The ICM strategy was based on a Farmer
Participatory Training and Research approach for adoption by cotton farmers. The project
was funded by the Common Fund for Commodities (CFC) and the European Union (through
its All ACP Agricultural Commodities Programme-AAACP) with in-kind contribution from
the governments of Kenya and Mozambique, and CABI.
Farmers in five districts in Nampula Province were selected for training on integrated crop
management (ICM) practices under the current project which was facilitated with funding
from the Common Fund for Commodities, EU and the Government of Mozambique through
a project initiative implemented by IAM, with CABI as the Project Executing Agency. The
purpose of the project was to improve cotton production efficiency through formulation and
promotion of ICM options in cotton production systems in Mozambique by involving closer
integration of private enterprise and public organizations. The project also established and
strengthened linkages within the value chain to ensure farmers had access to inputs,
technologies and information that would enable them produce more cotton competitively and
with greater profitability. The districts covered by the project were Monapo, Mecuburi,
Meconta, Ribaue and Lalaua. The project used a farmer field school (FFS) approach where
farmers were introduced to ICM practices. The FFS included both male and female farmers
and the average number of members was 25. The members worked together by sharing the
jobs involved in crop production after the training sessions, which were developed to
empower the cotton growers to undertake effective integrated crop management. The selected
ICM methodologies included use of spacing, intercropping, fertilizer (NPK and urea),
certified seed (CA 324), herbicides, agro-ecological system analysis and rational pesticide
usage
After the training, farmers established two plots where one was based on the conventional
methods while the second plot was based on the ICM practices. Farmers were also
encouraged to undertake similar practices on their own farms. In Mozambique cotton
production was undertaken under the concession system where different private cotton
companies were allocated certain specified areas, by the government, to support cotton
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production by supplying inputs and purchasing seed cotton produced in their area of
jurisdiction. Thus, Mozambique enforced a concession system that protected the ginning
company from competition for seed cotton. The activities conducted under the project
followed similar methods as those of contract farming. Participation of the cotton
agronomists and extension experts was therefore sought. Two cotton companies, OLAM and
SANAM, were involved in the initiative. In addition to training, the cotton growers were also
provided with cotton seed as was the case under the concession system and the companies
undertook to purchase all the cotton produced by the farmers. The cotton growers had regular
meetings to participate in the activities meant for cotton production, crop protection, postharvest handling and marketing.
Following the implementation of the activities it was considered necessary to establish the
extent to which the initiative helped the cotton farming community in the project areas to
improve productivity of cotton and the associated cotton incomes. Information pertaining to
the impacts of the project activities could also pave the way for up-scaling of the activities in
other cotton producing areas of the country. Hence an impact assessment was conducted with
the objectives listed below.
1.1 Objectives
1. Assess the extent of use of integrated crop management practices
Cotton growers were trained in respect to the use of proper spacing, intercropping,
agro-ecological system analysis (AESA) and rational use of pesticides in cotton
production. The assessment was made to establish how effectively these practices
were being used and how many of the farmers who had been trained were using the
practices
2. Examine the changes in productivity of cotton.
The main thrust of the project was to increase cotton yield and therefore examining
the changes in yield could indicate project related effects. Checking the area devoted
to cotton was also necessary to establish farmer perceptions with regard to cotton
production.
3. Establish level of use of pesticides in the project area
The project sought to promote rational use of pesticides with possible financial and
health benefits to the farmers. The frequency of use of pesticides as well as
expenditure on the pesticides was therefore assessed.
4. Measure the contribution of the ICM technologies to the farmers’ net income and
livelihoods
Farmers undertake farming as their main occupation. In this regard, the income
generated from cotton production is a key determinant of the welfare of the farming
community and how cotton is perceived in terms of contribution to their livelihoods
and overall welfare. Documenting the contribution of the ICM technologies would
give a clearer picture of the overall importance of the cotton enterprise
2.0 Methodology
2.1. Description of the study area
The study was conducted in five districts in Mozambique. The districts belong to Nampula
Province and two cotton companies (SANAM and OLAM) had been mandated to help in
cotton production and purchase the seed cotton produced in the same area. SANAM had 7
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districts under its jurisdiction and was more advanced in terms of value addition by
processing fibre, cooking oil and soap production compared to OLAM. SANAM also had
blocks of land where farming was conducted by groups whose land was ploughed by the
company and where production and marketing practices were monitored closely for
individual farmers after sub-division of the blocks. OLAM had similar arrangements as
SANAM. All farmers under the jurisdiction of a specified cotton company sold cotton to the
company. The companies provided seeds, pest control products, cash for production practices
and technical advice. Three districts; Monapo, Meconta and Mecuburi, under SANAM were
involved in the project. These districts were selected based on high number of cotton farmers
and the need to build farmer capacity in order to increase cotton productivity. OLAM had
jurisdiction over two districts, Ribaue and Lalaua; these were also involved in the project.
The selection of these two districts was based on high cotton production, strategic importance
to the company and importance of cotton to farmers involved in production.
As a comparison, similar districts for each of the companies involved in the project activities
were selected but these districts had not been part of the project. The comparison districts
were Muecate under SANAM Cotton Company and Murupula under OLAM Cotton
Company. The comparison districts had similar socio-economic and natural production
conditions as the project districts. Cotton production characteristics in each of the districts
were documented before the start of the project and at the end of the project. Impact
evaluation was conducted using a difference-in-differences method, which combined “beforeafter” and “with-without” analysis.
2.2. Sampling design
Purposive sampling and random sampling procedure were adopted for selecting the
respondents from the project districts and the comparison districts. Lists of the Farmer Field
Schools (FFS) that were formed in each district were obtained from the IAM agronomist in
Nampula. A random sample of two FFS was selected from each of the districts. Lists of
active members in the different farmer field schools (FFS) and other farmers in the same
village were obtained from FFS facilitators in the different districts. Using the lists an equal
number of trained FFS farmers and non FFS farmers living in the same district was randomly
selected from each of the participating project districts. The trained FFS farmers were those
who had taken part in the ICM training and who had continued to use these practices.
Another group of farmers was randomly selected from the control districts for comparison
with the project districts. The control districts were carefully selected at the start of the
project to ensure minimal possibility of information exchange with the project Districts. The
choice of the comparison districts was such that there would be minimal interaction with the
project districts to avoid “spill over” effects. This was because informal farmer-to-farmer
diffusion effects could blur the contrast between the comparison groups, causing an
underestimation of the effects of the project.
Fifty trained FFS ICM adopters and 50 non-FFS farmers were randomly selected from the
project districts, and fifty farmers were randomly selected from each of the comparison
districts. The comparison districts were under the same agro-ecological zones and production
practices as the project districts except that comparison districts did not have involvement or
contact with the project.
Purposive sampling was used for selecting the key informants. These were persons with
expert opinion drawn from different organizations. The greater majority of the key
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informants were the extension officers responsible for cotton production activities in different
areas. Agronomists from IAM delegation and lecturers in the faculty of agronomy also
provided information. One Focus Group Discussion (FGD) was conducted in each of the
districts studied.
2.3. Nature and source of data
The study used primary data which included variables such as age of the cotton growers, area
under cotton, methods of cotton production, types and quantities of inputs used in the
production of cotton, education level of the cotton growers, labour, and resource endowment.
The other data included crops grown, varieties grown, cotton output and sales, cotton
marketing, constraints in cotton production and marketing as well as the extent of use of the
integrated crop management practices. These data were collected by interviewing individual
cotton growers, focus group discussions and key informant interviews conducted through
structured questionnaires (Appendix 2), interview guides and checklists from September to
October 2013. The individual interviews and focus group discussions included farmers
involved in cotton production in the project and comparison districts. Key informant
interviews were conducted to generate expert opinion relating to cotton production,
processing and marketing in Mozambique. Expert opinion was necessary for cross checking
some of the information obtained from the cotton growers as well as providing specialist data
and information. The main sources of expert information were the extension officers who
were working closely with the cotton growers under the jurisdiction of the various concession
companies, and the representatives of the Ministry of Agriculture and the cotton companies.
One focus group discussion (FGD) was conducted in each of the districts to elicit farmer
perceptions of the various ICM practices that had been given to the farming community as
well as information on cotton production from the comparison district. Seven focus group
discussions were conducted with 12 farmers having an equal representation of men and
women. The FGDs enabled construction of spider web diagrams to assess impact of the ICM
practices. The FGDs also provided information to indicate the levels of capacity building
achieved through the project and an opportunity to cross-check information obtained from the
individual interviews.
2.4 Analytical techniques
The data collected were analysed using descriptive and inferential statistics. Tabular analysis
was followed to denote the basic characteristics of the sample with respect to growers’ socioeconomic profiles. Arithmetic means, percentages and frequencies were computed and
compared. The analysis of the data primarily consisted of working out the averages for
different variables to establish the difference among different districts. Estimates were
worked out per hectare for the purpose of making comparisons and drawing inferences.
Comparisons were made between the FFS members in project districts and the cotton
growers in the comparison districts using the difference-in-differences method (Gertler, et al.,
2011).
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3 0 Results and Discussions
3.1 Socio-economic characteristics of the cotton growers
The age of the cotton growers as well as the education levels, resource endowment and type
of house owned were assessed to give an indication of wealth status of the project
beneficiaries and the non-beneficiaries. No statistically significant differences (p>0.05) were
noted between the FFS members and the non-FFS members with regard to age and education
levels. In both categories the education levels were lower for the female farmers compared to
the male farmers. The general level of education did not show any significant differences
from the time of inception of the project and the time impact assessment was being
conducted. All the farmers studied had relatively low levels of education, which suggests that
the ideal methods for promoting the use of new technologies need to be more inclined to the
use of practical approaches. Similarly, household size and ages of the cotton growers did not
show significant changes over the project period.
Cotton was reported to be the key source of income and therefore required support to
improve productivity. Other crops were also cultivated in the area but the general view
among the farming community in the area was that cotton provided most of the income. The
highest ranking of cotton amongst other crop enterprises (Table 1) confirms the views of the
cotton growers in discussions. In Table 1, rank 1 refers to the highest contribution to crop
income, rank 2 refers to the second best contribution to crop income, etc., in terms of
contribution to income and the progression continues in descending order with respect to
contribution to income. The farmers’ views were also supported by both the focus group
discussions and the key informant interviews.
Table 1: Growers ranking of cotton and other crop enterprises
District category
Project Districts
Comparison Districts
Note:
Rank
1
2
3
4
1
2
3
4
% of growers giving the rank
Before the ICM practices After the ICM practices
68.6
96.5
24.0
3.5
3.5
3.9
73.0
79.8
8.0
18.2
14.0
2.0
5.0
-
1. A dash (-) means that the specified rank was not in the farmers’ ranking
2. The comparison districts did not use the ICM practices. Hence, “after the ICM practices” for the comparison
districts refers to the period after the project farmers had completed training and adoption of the ICMs
The rank given to cotton in terms of contribution to crop income indicates that the importance
of cotton was increasing. Cotton growers under the project appreciated the contribution of
cotton to income more than the farmers in the comparison districts. Table1 also indicates that
the importance of cotton could be increased by improving the farmer capacity in terms of
improvement of their production practices through training and where possible facilitating
farmer access to inputs. For the same period, the proportion of ICM farmers ranking cotton as
the most important source of income among the other crops was significantly higher than the
proportion of the Non-ICM cotton growers.
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The cotton growers in both the project and non-project districts were involved in farming as
the main activity. In the project districts there were no clear differences between the FFS
members and the non-FFS members regarding the type of house owned. The comparison
districts had relatively more farmers who owned traditional houses and less had semipermanent houses as compared to the ICM cotton growers (Fig. 1). Since the type of house
owned may indicate the level of wealth that an individual or household has, it was possible to
infer that there were some differences in wealth of the FFS members and the non-FFS
members. These differences suggest more benefits from improved and sustainable cotton
production using integrated cotton management practices. This assertion is consistent with
findings in Table 5.
Figure 1: Type of house owned by the ICM cotton growers and the non-ICM farmers
There were statistically significant differences between land owned across the different
districts (p<0.01) and land under cotton. No statistically significant differences exist between
land owned by male and female farmers (p>0.05) in the project and comparison districts. The
land ownership scenario is different for the male and female farmers when compared to the
time before the start of the project where men owned relatively larger land parcels. It was not
possible to attribute this change to the project given that it did not exclusively target policy
issues relating to land use and ownership in the project districts. From the project perspective
what was crucial was to generate a positive change in cotton productivity and income
obtained from the cotton enterprise.
3.2 Effect of integrated crop management practices
Farmers that were trained in the use of integrated crop management (ICM) practices in the
various districts had different views regarding the effects of the ICM practices that they had
been exposed to. The ICMs that the farmers were exposed to included use of proper spacing,
strip intercropping including maize and cotton, agro-ecological system analysis and rational
pesticide usage;. Alongside these practices there were some group dynamics in the farmer
field schools (FFS) relating to how to effectively work together. Participatory spider (web) or
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kite diagraming was used to visualize the results (Muller, et. al., (2010). Farmers were asked
to provide indicators they considered most important in assessing the effect of the ICM
practices.
After agreeing on the indicators, the farmers were asked to rate the extent to which the ICM
practices achieved them on a scale of 1 to 5 for two crop seasons, 2011-12 and 2012-13. The
farmers also had an opportunity to discuss the reasons for the changes. In the rating scale,
zero was considered the base period. The range between zero and one was the transition
stage. One (1) rating represented initial use/effect levels which were very weak while five
represented efficient/effective use that was considered to be very good. Two represented
weak, three represented moderate and 4 represented good. The indicators included cotton
yield, usage of the various inputs especially the pesticides, crop production skills, group
development, planning of tasks and cotton income. Issues discussed under crop production
skills included knowledge of and ability to conduct Agro-Ecological System Analysis
(AESA), use of a combination of crop management practices and when to use different crop
production practices, such as intercropping. In the case of group development the farmers
considered group dynamics, team work, group cohesion, interrelationships, interactions and
exchange of information. Pesticide usage was discussed in terms of rational pesticide use that
is the extent to which there was a reduction in the use of pesticides. Household cotton
income was assessed in terms of ability to sell more and receive more income for the
different seasons that were assessed. Discussions about planning related to early preparation,
use of different methods, identifying when, where and how to obtain the necessary resources
for cotton production.
The general view was that the ICM practices would help in improving cotton productivity but
to different extents. The capacity building efforts undertaken improved the farmers’ level of
interaction with fellow farmers and other cotton stakeholders. All the practices were guided
by trained ICM facilitators from the cotton companies and IAM. Consequently, the company
staffs were expected to follow-up on the practices under their normal routine of helping to
improve cotton production in the areas under their jurisdiction.
The cotton growers in Monapo District noted that there was more organized and consistent
use of the integrated pest management practices including the correct spacing, and checking
for the pests and diseases following the training that was offered through the project (Fig. 2).
The use of proper cotton spacing was noted as a good activity and the cotton growers showed
a lot of interest scouting for the pests before application of the pesticides. It was noted that
due to regular interaction with the company staff who facilitated the FFS, there was some
degree of understanding between the cotton growers and the company agents regarding how
cotton was purchased and the computations of the costs and the net payments to the farmers.
There was some improvement in yield attributed to the use of good crop production practices.
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Crop production skills
5
4
Planning
3
Yield
2
1
0
Cotton income
Pesticide Usage
Group development
Season 2011/2012
Season 2012/2013
Figure 2: Rating of the effects of the project in Monapo District
In the case of Meconta District, the cotton growers were able to effectively undertake
intercropping and good planning was noted among the group members that led to effective
sharing of roles. Discussions with the cotton growers revealed that there was no tangible
change in the use of pesticides between the two seasons under reference (Fig. 3). Use of agroecological system analysis before embarking on the use of crop protection chemicals was
noted as a result of the training in ICM but did not convert to clear reduction in the use of
pesticides. Capacity building through the project facilitated cotton growers to appreciate the
use of different approaches in cotton production. All the farmers that participated in the focus
group discussion in the district reported that they had been able to undertake intercropping
with maize, while 50% reported having been involved in the use of all the integrated pest
management approaches especially proper crop spacing.
Figure 3: Rating of the effects of the project in Meconta District
The cotton growers in Mecuburi District had similar experiences from the ICM training that
was provided through the farmer field schools in the district under the project (Fig. 4). The
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cotton growers noted that their crop production skills improved tremendously especially with
respect to AESA, crop spacing and intercropping. The cotton growers received good crop
incomes possibly due to the good yield received during the second season. Providing some
gross margins would allow the cotton growers to further appreciate the difference in incomes
between the current production methods and use of the ICM practices and hence encourage
them to get more involved in the use of the ICM practices.
Figure 4: Rating of the effects of the project in Mecuburi District
In the case of Lalaua District the cotton growers reported that they were able to reduce the
amount of pesticides used in cotton production (Fig. 5) due to the use of the ICM practices.
Cotton yield was also reported to have increased due to the ICM training. The members of
the farmer field schools noted that the activities enabled them to interact better with their
colleagues and exchange ideas and hence improve on planning and sharing of roles.
Figure 5: Rating of the effects of the project in Lalaua District
The cotton growers in Ribaue reported that the ICM training generated improvements in yield
and the use of proper spacing and integrated pest management through scouting for pests
followed by spraying after establishing the threshold levels (Fig. 6). The effect on planning
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was noted to be the same as for group development, which involved sharing of roles. The
farmers reported an improvement in the cotton income attributed to timely collection of the
produce and transparent weighing. There was good interaction between the cotton growers
themselves as well as the cotton growers and the representatives of the cotton companies. The
good interactions improved the cotton growers’ access to crop production and marketing
information.
Figure 6: Rating of the effects of the project in Ribaue District
All the districts and the participating farmers reported that the capacity building through the
training in ICM enabled the cotton growers to change their production practices. A general
trend noted was the use of intercropping, spacing and the reduction in the use of pesticides.
There was an integration of good farming practices by some of the participating farmers in
the areas under the project. This demonstrates willingness by the cotton growers to learn and
practice new cotton productions skills to improve cotton productivity. Given the relevant
support the cotton growers could change their production practices in line with the required
productivity needs.
The cotton growers noted that they obtained good skills in sowing, particularly spacing
between and within plants. This was complemented by the fact that the farmers appreciated
the need to weed earlier that is before serious weed infestation that also facilitated infestation
by insect pests. There was also an increase in knowledge regarding how to use traps such as
sugar to attract pests. Methods of proper spaying after scouting for the pests were also learnt
by the cotton growers. All these changes were reported to be associated with an increase in
the cotton yields and hence the amount of seed cotton sold to the cotton companies.
3.3 Cotton production and productivity
Cotton production was based on a zoning (concession) system. The private company in a
certain territory promoted cotton by supplying seed for planting, inputs on credit, technical
extension service, and procured all the seed cotton produced from the designated area. This
was a legal obligation involving the cotton companies as signatories to the concession
contracts with the Government of Mozambique. The farmers received guaranteed seeds free
of charge. This was not certified seed, but in a few cases seed was produced under contractual
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arrangements, where the companies selected an area where they contracted farmers who
multiplied the seeds. Some of the seeds supplied to the farmers were coated with systemic
insecticides against early season pests e.g. jassid and aphids. Farmers paid for the coated
seeds. The cotton companies also provided crop protection chemicals to the cotton growers
under their jurisdiction. The laws governing cotton production and zoning were still as before
the initiation of the project activities. The project initiative did not cover policy relating to
production and zoning, rather the intention was to increase the productivity of cotton. The
project facilitated farmers’ access to seeds through the appropriate liaison with the cotton
companies allocated different locations for cotton production.
Farmers undertook cotton production using hand hoes. In a few cases tractors were used to
undertake cotton production mainly through support of the cotton companies in the area. The
cotton variety grown was CA 324. Hand weeding was practiced. Pests and diseases were
controlled by spraying pesticides.
The land allocated to cotton production increased in more than half of the project areas after
the ICM initiatives. In two districts, Lalaua and Ribaue, there was a decline in area devoted to
cotton after the ICM initiatives (Fig. 7). Lalaua and Ribaue joined the ICM initiatives much
later and it is possible that the effects of ICM practices had not yet been appreciated by the
farming community to encourage more cotton growers to devote land to cotton production.
There was some decline in area under cotton in Murupula District and no change in area
under cotton in Muecate District, both of which were comparison districts. Two other issues
were also identified in the study. Firstly, cotton productivity was affected by lack of the
necessary production skills and support, meaning that more technical and material support
was required to facilitate cotton production. Also, it was possible to infer that if measures
would not be taken to help in the production practices of cotton then the area under cotton
could continue to decrease thereby reducing the competitiveness of cotton. The second
assertion is based on the decline in area under cotton in one control district and the
participating district that had not been adequately exposed to the ICM practices and other
support.
137
3.0
Land size (Ha.)
2.5
2.0
1.5
1.0
0.5
0.0
Lalaua
Ribaue
Monapo
Meconta
Before ICM
Mecuburi
Murupula
Muecate
After ICM
Figure 6: Land under cotton production in the project and control (Murupula and Muecate)
Districts
Note: After ICM for the comparison districts refers to the period after the project districts had
completed implementing the ICM practices
In most of the districts there were increases in the yield of cotton after the adoption of the
ICM practices. The cotton yields were better than those before the growers started using the
ICM practices (Table 2). There were significant differences (p<0.05) in yields between the
project districts and the comparison districts indicating that the ICM practices had a good
contribution to increasing the cotton yields. The cotton yields from the ICM farmers were
better than those from farmers that did not use the practices. This means that the cotton
growers were likely to benefit from the ICM practices. Given the production potential and
productivity differences it is possible to increase cotton production in areas where there is
low production.
Table 2: Cotton production in the different districts on the farmers’ own fields (kg/ha.)
Name of District
cotton
company
SANAM Mecuburi
Meconta
Monapo
Muecate*
OLAM Lalaua
Before
the
project
(a)
474.8
494.3
595.9
428.5
510.8
After
the
project
(b)
752.4
557.5
674.5
455.9
641.7
Differences
(Yield after
ICM less
before ICM)
(c)
277.6
63.2
78.6
27.4
130.9
138
Difference-indifferences
(ICM less
Comparison)
(d)
250.2
35.8
51.2
32
%
Change
in yield
(e)
(d/a)*100
52.7
7.2
8.6
6.3
Name of District
cotton
company
Before
the
project
(a)
After
the
project
Differences
(Yield after
ICM less
before ICM)
(b)
(c)
Ribaue
432.2
554.3
122.1
Murupula*
411.9
510.8
98.9
Note: 1. *=Comparison district
2. After ICM for the comparison districts refers to the
had completed implementing the ICM practices
Difference-indifferences
(ICM less
Comparison)
(d)
23.2
-
%
Change
in yield
(e)
(d/a)*100
5.4
-
period after the project districts
There were no significant differences (p>0.05) in yield between the ICM adopters and the
non-FFS farmers in the project districts. This may be because of information spill over to the
non-FFS farmers in the project districts. The diffusion effect lends support to the fact the
ICM practices promoted were preferred by the farmers. It also indicates that FFS generated
an environment that facilitated exchange of information and skills.
The cotton growers whose ICM practices capacity had been built through the project
demonstrated good production practices and post-harvest handling of the cotton. They also
had improved communication amongst themselves as opposed to the other cotton growers.
The interaction could help the cotton growers to negotiate better with the cotton companies
that serve the areas where they undertake cotton production activities. Cotton was packed in a
better manner in the fields of the ICM farmers although the sorting and grading of cotton did
not show major differences between the ICM adopters and the non-ICM adopters. However,
adopters of the ICM practice did demonstrate improved capacity to source information for
use as appropriate.
The production scenario was much better in the plots used by FFS. A key observation was
that the ICM plots had better yields compared to the conventional practice (Table 3). The
ICM plots had significantly higher yield compared to the farmer practice in all the districts
and in all the farmer field schools (p<0.05). This underscores the importance of building
farmer capacity through training in the use of the ICM practices.
139
Table 3: Cotton production in the farmer field schools (kg/ha)
ICM Plots
Name of
cotton
company
SANAM
OLAM
District
Mecuburi
Meconta
Monapo
Lalaua
Ribaue
Conventional plots
(Farmer practice)
Season 1 Season 2
Season 1 Season 2
(2011/1 (2012/2013 (2011/12) (2012/13)
2)
)
869.2
746.8
441.4
602.0
643.0
720.0
437.0
388.0
823.3
711.0
398.0
635.5
772.7
784.1
530.0
627.3
800.0
888.8
497.6
550.0
3.4 Pesticide usage in the study area
All the pesticides used were provided by the cotton companies in the project area. The
companies directed the farmers on the methods of using the pesticides and indicated the
purposes for which the pesticides were to be used. The key pesticides used included
Volamiprid, Zakanaka Top, Zakanaka K and Zakanaka Pro. Focus group discussions revealed
that the ICM farmers spend less on the pesticides and the frequency of use of the pesticides
was relatively lower among the ICM cotton growers. Individual farmer interviews also
revealed a reduction in pesticide usage among the project farmers (Table 4). The reduced
frequency in pesticide application by the ICM cotton growers could have been due to the
timely control made possible through the use of agro-ecological system analysis. Pest and
disease incidence levels were reported to have declined despite the reduction in the use of
pesticides.
Table 4: Expenditures (money spent) on pesticides (Mt/ha.)
Name of District
cotton
company
Before After
the
the
project project
(a)
(b)
Difference
(Expenditure
after ICM less
before ICM)
(c)
-124.1
-18.8
-160.6
15.3
-180.8
-160
97.4
Difference-in% Change
differences
in
(ICM less
Expenditure
Comparison)
(e)
(d)
(d/a)*100
-139.4
-31.8
-34.1
-7.8
-175.9
-38.0
-278.2
-54.4
-257.4
-47.2
-
SANAM Mecuburi
438.5 314.4
Meconta
435.3 416.5
Monapo
462.4 301.8
Muecate*
350.7
366
OLAM
Lalaua
511.4 330.6
Ribaue
545.8 385.8
Murupula* 362.2 459.6
Note: 1. *=Comparison district
2. After ICM for the comparison districts refers to the period after the project districts
had completed implementing the ICM practices
The comparison districts had relatively higher expenditures on pesticides compared to the
project districts. Only Meconta District had average expenditures on pesticides that were
140
higher than those in the comparison district under the same cotton company. In spite of the
expenditure in Meconta being high, it was still lower than the time before the ICM project,
which still supports the view that the ICM practices contributed to a reduction in expenditure
on pesticides. The general low pesticide expenditure in the project districts and for the
farmers using ICM suggests a more rational pesticide usage among those trained in ICM. In
spite of the improved/efficient use of pesticides following the project initiative, the ICM
adopters experienced some difficulties in accessing pesticides and using them. The sprayers
and the batteries for the sprayers were not readily available. The sprayers were shared by
many farmers involved in cotton production. These constraints also affected the non-ICM
farmers. It is suggested that the Concession Companies provide more sprayers and the
accessories to try to alleviate these problems. Farmers may also pool resources on their own
to purchase the sprayers and the accessories.
3.5 Contributions of the ICM to farmers’ income
The processes involved in cotton marketing did not change as a result of the use of the ICM
technologies. Cotton was normally purchased by the companies that were located in specific
areas that were allocated by the government. These companies supplied inputs under an
arrangement with the farmers for them to purchase the cotton once harvested. According to
farmers interviewed, although the companies were mandated to supply the inputs, provide
technical knowhow and purchase the seed cotton; the services offered did not meet the
expectation of the farmers. The returns to cotton production demonstrated an improvement
for the cotton growers that participated in the ICM activities (Table 5). Different incomes
were reported by the different farmers in the different districts, which again indicated a
possibility of improving income received within the different districts.
Table 5: Net income per ha from cotton production (Metacais)
Name of District
cotton
company
SANAM Meconta
Mecuburi
Monapo
Muecate*
OLAM
Lalaua
Ribaue
Murupula*
Before
the
project
(a)
6281.9
4246.5
4000.5
3648.4
5538.0
5121.2
3500.6
After
the
project
(b)
8831.8
5980.6
4390.2
3946.5
5872.3
5430.5
3698.4
Difference
(Income after
ICM
less
before ICM)
(c)
2549.9
1734.1
389.7
298.1
334.3
309.3
197.8
Difference-indifferences
(ICM less
Comparison)
(d)
2251.8
1436.0
91.6
136.5
111.5
-
%
Change in
income
(e)
(d/a)*100
35.8
33.8
2.3
2.5
2.2
-
Note: 1. *=Comparison district
2. After ICM for the comparison districts refers to the period after the project districts
had completed implementing the ICM practices
Given similar agro-ecological zones and the input and technical support from the cotton
companies it is possible to increase the net income from cotton production in the districts that
received low net incomes. In all the project participating districts, levels of net income were
higher for the farmers that adopted the ICM practices compared to the other farmers in the
same district. This may be associated with rational input use attributed to the ICM training
141
reducing farmer costs. The results indicate that the use of ICM practices was likely to
increase net incomes from cotton production which in turn suggests that the cotton growers
need to be encouraged to use the ICM practices. Net cotton income from the farmers in the
comparison district was lower than that of the farmers that used the ICM and those in the
project districts. This may suggest that the farmers trained in ICM practices gained some
experience that may have led to the use of improved practices, which generated better yield
and hence more income. It also suggests a possibility of exchange of information and
diffusion of skills on good agricultural practices between the farmers in the FFS and non-FFS
members. This underscores the need for capacity building in cotton agricultural production
practices.
Improved cotton income received by the farmers that adopted the ICM practices could be
used to purchase household requirements and thereby improve the livelihoods of the cotton
growers. This is crucial given that the cotton growers had limited alternative income
generating activities.
4.0 Conclusions
Impact assessment was conducted to establish the effects of the Integrated Crop Management
(ICM) training and associated services offered to the cotton growers in Nampula Province,
Mozambique. The assessment established the extent of use of the integrated crop
management practices, changes in productivity of cotton, level of use of pesticides and the
contribution of the ICM technologies to the farmers’ incomes. The ICM practices were used
to different extents by the cotton growers in the different districts. Intercropping, rational use
of pesticides and proper spacing of cotton were the most preferred ICM by the farming
community. Intercropping, although noted to be a key ICM practice was less used by the
farming community in Mozambique. Given the need for provision of different options for
purposes of improving cotton productivity it is necessary for the cotton farmers to be advised
on the importance of intercropping. The rational use of pesticides by the ICM farmers in the
project areas as demonstrated by less expenditure on pesticides suggests the need for upscaling the training to other cotton growers.
The cotton yields received by the ICM cotton growers were relatively higher than those of the
non-ICM cotton growers. This demonstrates the importance of the ICM practices to yield.
There is a need therefore to extend the ICM practices to the other cotton farmers. Scaling-up
of the practices need to be accompanied with the formation of active and effective groups that
are legally constituted to be able to source for other services. This is attributed to the fact that
the farmer field school members indicated in individual interviews and FGDs that they were
better able to interact with the cotton companies as a group. Interactions among the cotton
growers established ownership of services and better planning.
The ICM practices had a significant effect on cotton growers’ incomes in addition to better
yields. Costs were reduced in ICM plots especially due to reduction in pesticides. Farmers
could make better use of the benefits obtained from the use of ICM by undertaking cotton
production as a business activity. In this regard, activities that enhance business undertaking
need to be integrated. Among these are coordinated appropriate record keeping and
budgeting. The members of the farmer field schools noted that they were able to plan and
work effectively as a team. This suggests that training in group dynamics may be a key to
assuring the pooling of resources by the farmers and hence encourage group production as
well as information sharing among the group members. The groups formed need to be
142
encouraged to operate in a manner that is consistent with the operations of innovation
platforms in order to be able to interact effectively.
The cotton enterprise is a key contributor to the incomes of the farming community in the
project area. However, a relatively lower proportion of land is devoted to cotton production.
During the project period there was some increase in the land devoted to cotton production as
was the increase in cotton yield and income. This indicates that there is potential for
increasing the area under cotton production and productivity. It is necessary to provide more
technical know-how to the cotton growers coupled with promotion of cotton as a profitable
enterprise.
143
5.0 References
Duncan Boughton, David Tschirley, Ballard Zulu, Afonso Osorio Ofiço, Higino Marrule.
2003. Paper prepared for presentation at the 25th International Conference of
Agricultural Economists, August 16-22, 2003, Durban, South Africa
Francesca Mancini, Ariena H.C. Van Bruggen and Janice L.S. Jiggins. 2007. Evaluating
Cotton Integrated Pest Management (IPM) Farmer Field School Outcomes Using the
Sustainable Livelihoods Approach in India. Expl. Agric. (2007), Volume 43, Pp. 97–
112
Gérald Estur. 2008. Quality and Marketing of Cotton Lint in Africa Working Paper Series
No. 121, October 2008
Gertler, Paul J., Sebastian Martinez, Patrick Premand, Laura B. Rawlings and Christel M. J.
Vermeersch. 2011. Impact Evaluation in Practice. The World Bank: Washington DC
Müller Irene, Dominique Guenat and Ingrid Fromm. 2010. Impact monitoring and evaluation
system for Farmer Field Schools in Kyrgyzstan: How to optimize resource allocation
for higher impact. Journal of Agricultural Extension and Rural Development
2(10):211-218. Available online http:// academicjournals.org/JAERD
MOA/MSU. 1993. Evolution of the Rural Economy in Post-War Mozambique: Insights from
a Rapid Appraisal in Monapo District of Nampula Province. Working Paper No. 16
Moses M. Ikiara and Lydia K. Ndirangu. 2003. Developing a Revival Strategy for Kenya’s
Cotton-Textile Industry: A Value Chain Approach. Kenya Institute for Public Policy
Research and Analysis. KIPPRA Working Paper No. 8, January 2003
144
Appendices
Appendix 1: Project areas in Mozambique
145
I.2.
Appendix 2: Post
Questionnaire
adoption
individual/household
socio-economic
survey
Section A: Identification
Date ……………………District: ………..…….. Administrative Post (Division) ……………………
Locality (Location) ……………………. Sub-location …………….Village/Regulado ………..………
Area of Influence/Agency …………………………………………………………….…………………
Name of Facilitator/enumerator: …………………………………………………….…………………
Name of farmer field school (FFS only) ………………………………..……….…………………….
Farmer adopted ICM (FFS only): 1=yes, 2=no ………………………………………………………...
Name of farmer: ……………….…….……………..…………...……………………………..…….…
Section B: Household and socio-economic characteristics
1. Age of the farmer: ……………..years
2. Gender of the farmer (circle as appropriate): Male=1, Female=2
3. Highest formal education attained by the farmer (circle answer): non-formal education=1,
Primary=2, secondary=3, University=4, other (specify)...………………
4. Total size of land owned by the farmer (ha) -----------------------------------------------------5. Type of house owned (tick answer): 1=permanent, 2= semi-permanent, 3=traditional where:
Permanent = a stone-walled house roofed with iron sheets/tiles and has a stone slab
Semi-permanent = a brick/timber/off cut walled house roofed with iron sheets and has a stone slab
Traditional = a mud or other local material walled house thatched with grass or any other locally available material and has earthen slab
6. Has there been an increase in the number of the assets (cows, oxen, goats, motor cycles, cars,
chicken, donkey, wheel burrows, etc.) that you own in the last three years? 1=yes, 2=no
7. If yes, what has caused the change? …………………………………………………………………
8. How many of your fellow farmers (neighbours) who are not members of the FFS have
adopted the ICM technologies? (Question for FFS members only) ------------------------9. In the table shown below please list and rank in order of importance five major crops/ enterprises
(including cotton) that you were involved in the last crop season (2012/13) you grew cotton,
annual income from each and rank (prioritization of cotton as an income earner).
Crop/enterprise
Area
(ha)
Annual
production
(kg)
Price per
unit (e.g.
kg)
Annual
income (MT)
Ranking
Section C: Cotton production
1. State the total area under cotton in the last season (Ha.) ….…………………………………….….
2. In the table shown below please state the cotton variety and the methods (technology) that you were
using to undertake production of the specified variety three years ago (MZ:before 2010/11 season,
KE:before 2010 season ) and now. (Technologies include: IPM (crop rotation, strip intercropping),
spacing, herbicide usage, certified seed, fertilizer application, mixed cropping, pure stand.
Cotton
variety
Last season
Crop
management
technology
used three
years ago
Crop
management
technology used
now
Area under the
specified variety
last season (Ha)
Cotton
production
last season
(kg)
3. Give reasons why you practice the current crop management strategy indicated in question
number 2 above ---------------------------------------------------------------------------------------4. Please state problems associated with each of the crop management strategies
5. Please state the benefits obtained from using the crop management strategies listed above
146
6. Indicate who, when and how the following activities are done in cotton production?
Activity
When (Month) Who* How**
Remarks
Land preparation
Planting
First weeding &
thinning
Second weeding
Third weeding
Spraying chemicals
Harvesting
Transportation
Cotton selling
Decision on cotton area
*Who: 1=Men, 2=Women, 3= Girls (7-18years), 4=Boys (7-18years), 5=All listed
**How: 1= Hand 2=Animal draft power 3= Tractor
Others (Specify)………
7. In the table shown below please indicate the types, quantities and costs of the inputs used in cotton
production in the last season.
Type of input
Quantity
Units ((litres/
millilitres/
kg/ no )
Cost
Frequency of
use now (with
ICM practice)
Frequency of use 3
years ago (before
ICM practice)
Seeds
Pesticides:
1. Volamiprid
2. Zakanaka Top
3. Zakanaka K
4. Zakanaka Pro
Herbicides
Fertilizers
Farm yard manure
Land preparation labour days: Family
Hired
Planting labour days: Family
Hired
Thinning labour days: Family
Hired
Weeding labour days: Family
Hired
Spraying labour days: Family
Hired
Harvesting labour days: Family
Hired
Transportation
Other (specify)
8. What problems are associated with input acquisition? ……………………………………….
9. Do you have any contractual arrangements for cotton production with a company? Yes=1 No=2
10. If yes Please specify the contractual arrangements that you have for cotton production and
marketing --------------------------------------------------------------------------------------------------11. Please state the benefits obtained from the contractual arrangements --------------------12 Please explain how cotton is handled after harvesting (sorting, grading, etc.) -------------------13. Please indicate the constraints you face in cotton production:
Diseases and pests: --------------------------------------------------------------------------------------------Inputs and equipment: ----------------------------------------------------------------------------------------Marketing related: ----------------------------------------------------------------------------------------------
147
Section D: Cotton Pest and disease control
1. Please state the different methods that you used for the control of diseases and pests and the costs
involved.
Method used three years ago
Costs three years
Method used now
Costs now
2. What problems do/did you encounter in the control of cotton pests and diseases? ------------------3. Please suggest methods for improving adoption of the improved cotton production methods (ICM
technologies for FFS members only) ------------------------------------------------------------------------4. Please suggest methods for improving cotton production
Section E: Marketing of cotton
1. How much cotton did you harvest in the last season (kg)?
2. Please state the quantity of cotton sold in the last crop season and the price per unit
1st Grade cotton ------------------ kg/bags Price per kg/bag (delete as appropriate) -------------2nd grade cotton -------------------kg/bags Price per kg/bag (delete as appropriate) ------------3. Are there any price differences for the cotton produced using the improved methods (ICM) and that
produced using other methods? 1=yes, 2=no ----------------------------------------------------------4. What is the current farm gate price for cotton? (Please specify unit and price per unit)
Price per kg of 1st grade -------------Price per kg of 2nd grade -------------5. Please specify the type of costs involved in cotton marketing and the actual amounts
(E.g. transportation, gunny bags, packaging, loading, unloading, --------------------------------------6. Please indicate the problems you encounter in cotton marketing: poor seed cotton prices=1, low
seed cotton volumes=2, long distance to ginning facility=3, others (specify)
7. Please suggest methods for improving cotton marketing --------------------------------------------------8. How do you rate the information flow between you and the other cotton stakeholders now
compared to 3 years ago? 1=improved, 2=same, 3=worsened
Researchers -------------------------Fellow cotton farmers--------------Cotton ginners -----------------------IAM delegation -----------------------
148